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Three questions must be answered to optimize any openhole sampling program. These questions are where to sample, when to sample, and how to sample. Samples must be acquired from the right locations in order to answer the critical questions posed by the asset evaluation and production teams. Samples must be obtained at the right time to minimize contamination while using valuable rig time efficiently. Samples must be taken in a manner that provides the laboratory with the most representative analysis of the subsurface reservoir fluid. Carbon dioxide is a corrosive acidic gas component often found in petroleum reservoirs. Special and relatively costly completion and production equipment is required to produce reservoir fluids containing carbon dioxide. Carbon dioxide must be scrubbed from petroleum before that petroleum is shipped. Carbon dioxide may cause flow assurance issues with regards to scale of inorganic and organic components, thereby requiring costly mitigation. An accurate estimate of carbon dioxide concentration in the reservoir fluid is required to make an accurate determination of the cost of CO2 remediation. New formation tester carbon dioxide analysis technology has allowed detailed examination of these questions due to a previously unobserved phenomenon with respect to formation tester sampling and carbon dioxide. Specifically, carbon dioxide may bind with caustic components of drilling-fluid filtrate in either a reversible manner or be consumed by caustic components in an irreversible manner. Observation of a reversible reaction has been used to validate the phenomena but also provides a cautionary warning that for different chemical reactions in which carbon dioxide may be consumed, openhole samples may significantly underestimate the amount of carbon dioxide in the reservoir fluid. New sampling procedures applicable to existing formation testing infrastructure mitigate this sampling issue by determining the correct carbon dioxide content in the reservoir fluid. The new sampling procedures are validated with the carbon dioxide monitoring technology but are not strictly dependent on it. In addition, the proposed sampling procedures are applicable to the measurement of all reactive petroleum components, such as hydrogen sulfide.

Digital fluid sampling is a technique utilizing downhole sensors to measure formation fluid properties without collecting a physical sample. Unfortunately, sensors are prone to drift over time due to the harsh downhole environmental conditions. Therefore, constant sensor evaluation and calibration is required to ensure the quality of analysis. A new technique utilizes a virtual sensor as a digital twin which provides a calibration that can be utilized by the physical twin. Digital twin technology enables the end-user to operate and collaborate remotely, rapidly simulate different scenarios, and provide improved accuracy via enhanced up-to-date calibrations. With respect to downhole fluid identification, the contribution of harsh environmental conditions and sensor drift can also be mitigated by realizing a virtual implementation of the fluid behavior and the individual sensor components. Historically, the virtual behavior of a digital twin has been constructed by a combination of complex multi-physics and empirical modeling. More recently, access to large datasets and historical results has enabled the use of machine learning neural networks to successfully create digital twin sensors. In this paper, we explore the efficacy of constructing a digital twin on a single downhole optical fluid identification sensor using both the machine learning nonlinear neural network and the complex, multi-physics' based modeling approaches. Advantages and lessons to be learned from each individual method will be discussed in detail. In doing so, we have found a hybrid approach to be most effective in constraining the problem and preventing over-fitting while also yielding a more accurate calibration. In addition, the new hybrid digital twin evaluation and calibration method is extended to encompass an entire fleet of similar downhole sensors simultaneously. The introduction of digital twin technology is not new to the petroleum industry. Yet there is significant room for improvement in order to identify how the technology can be implemented best in order to decrease costs and improve reliability. This paper looks at two separate methods that scientists and engineers employ to enable digital twin technology and ultimately identify that a hybrid approach between machine learning and empirical physics'-based modeling prevails.

Multivariate optical computing (MOC) is a compressed sensing technique enabling the measurement of analytes in a complex interfering mixture under harsh conditions. In this work, we describe the design, modeling, fabrication, and validation of a sensor for the measurement of dissolved methane in petroleum crude oil at high and variable combinations of pressure (up to 82.727 MPa) and temperature (up to 121.1 °C). Both laboratory and field validation results are presented, with five separate MOC sensors yielding a RMS error of 0.0089 g/cm3 methane in high pressure/high temperature laboratory and field samples compared to 0.0086 g/cm3 methane for a room temperature laboratory Fourier transform infrared (FTIR) spectrometer using partial least-squares (PLS) regression models.

Background: There has been a renewed interest in ulnar collateral ligament (UCL) repair in overhead athletes because of a greater understanding of UCL injuries, an improvement in fixation technology, and the extensive rehabilitation time to return to play. Purpose/Hypothesis: To evaluate the clinical outcomes of a novel technique of UCL repair with internal brace augmentation in overhead throwers. Study Design: Case series; Level of evidence, 4. Methods: Patients undergoing a novel technique of UCL repair with internal brace augmentation were prospectively followed for a minimum of 1 year. Potential candidates for repair were selected after the failure of nonoperative treatment when imaging suggested a complete or partial avulsion of the UCL from either the sublime tubercle or medial epicondyle, without evidence of poor tissue quality of the ligament. The final decision on UCL repair or traditional reconstruction was determined intraoperatively. Demographic and operative data were collected at the time of surgery. Return to play, and Kerlan-Jobe Orthopaedic Clinic (KJOC) scores were collected at 1 year and then again at 2 years postoperatively. Results: Of the 111 overhead athletes eligible for the study, 92% (102/111) of those who desired to return to the same or higher level of competition were able to do so at a mean time of 6.7 months. These patients had a mean KJOC score of 88.2 at final follow-up. Conclusion: UCL repair with internal brace augmentation is a viable option for amateur overhead throwers with selected UCL injuries who wish to return to sport in a shorter time frame than allowed by traditional UCL reconstruction.

Accurate reservoir fluid identification and sampling of hydrogen sulfide (H2S) contaminated fluids is difficult to achieve due its consumption by the interior of downhole tool surfaces prior to sampling or measurement. For low PPM level concentrations, this fact does not change, despite recent tool advances utilizing NACE compliant materials. Consequently, H2S concentrations are typically under-reported which adversely affects production and presents significant health safety and environment concerns. Historically, only sampling bottles have been coated to preserve H2S concentrations during transit to laboratories with a material that is resistant to H2S reactivity to enable more representative measurements. However, only very recent efforts have transitioned the focus toward successfully coating the interior of the tools. This paper details a state-of-the-art technology, initially developed and heavily leveraged from the semiconductor industry. The technology is adapted to coat the interior surfaces of downhole tools with a chemically resistant dielectric thin film. New developments now provide the benefit of the process being safe, able to be performed at atmospheric pressure and temperature conditions, and portable; thus, allowing the coating process to be deployed to field locations. The method involves atomic layer deposition (ALD) technology to be plumbed in directly to a downhole tool and conformally deposit a thin layer (e.g. < 1 micron) of highly durable H2S-resistant sapphire to the entire interior tool surface. An automated procedure has been developed allowing the versatility to accommodate a number of unique geometries inherent of different formation tester configurations. New advances in Quartz Crystal Microbalance sensors are also realized in-situ to optimize (in real-time) the efficiency of the process and ensure uniform and conformal coverage is obtained in the fastest and safest manner. Laboratory testing on a prototype system demonstrated uniform and conformal coverage of a ~ 500 nm thick sapphire film resistant to flaking and scratching. Accelerated lifetime stress testing demonstrated high durability relative to expected tool life. Testing of coated and uncoated tools show the coating is successful at the 50ppm level H2S for up to 4 days. These results are contrasted with similar tool body samples not coated with the H2S-resistant ALD sapphire and subject to the same H2S conditions. To show the coating’s durability, subsequent experiments flowed mud-based drilling fluid through both the tool body and sample chambers, followed by thorough cleaning and successful repeating the same 50ppm H2S test. Exposure of the sapphire coated tool body and sample chambers to various concentrations of H2S demonstrated zero loss. Ultimately this technique represents a new opportunity to gather representative formation samples containing low concentrations of H2S.

Downhole fluid analysis has the potential to resolve ambiguity in very complex reservoirs. Downhole fluid spectra contain a wealth of information to fingerprint a fluid and help to assess continuity. Commonly, a narrowband spectrometer with limited number of channels is used to acquire optical spectra of downhole fluid. The spectral resolution of this type of spectrometer is low due to limited number of narrowband channels. In this paper, we demonstrate a new type, compressive sensing (CS) based broadband spectrometer that provides accurate and high-resolution spectral measurement. Several specially designed broadband filters are used to simplify the mechanical, electrical, optical, and computational construction of a spectrometer, therefore provides measurement of fluid spectrum with high signal-to-noise ratio, robustness, and a broader spectral range. The compressive sensing spectrometer relies on reconstruction technique to compute the optical spectrum. Based on a large spectral database, containing more than 10000 spectra of various fluids at different temperature and pressure conditions, which were collected using conventional high resolution spectrometer in a lab, the basis functions of the optical spectra of three types of fluids (water, oil and gas/condensate) can be extracted. The reconstruction algorithm first classifies the fluid into one of three fluid types based on multichannel CS spectrometer measurements, the optical spectrum is reconstructed by using linear combination of the basis functions of corresponding fluid type, with weighting coefficients determined by minimizing the difference between calculated detector responses and measured detector responses across multiple optical channels. The reconstructed data may then be used for purposes such as contamination measurement, fluid property trends for reservoir continuity assessment, and digital sampling. Digital sampling is the process of extrapolating clean fluid properties from formation fluids not physically sampled. The reconstruction spectrum covers wavelengths from 500 nm to 3300 nm, which is a wider spectral region than has historically been accessible to formation testers. The expanded wavelength range allows access of the mid-infrared spectral region for which synthetic drilling-fluid components typically have higher optical absorbance. This reconstruction spectra may allow contamination to be directly determined. This paper will discuss the CS optical spectrometer design, fluid classification and spectral reconstruction algorithm. In addition, the applicability of the technique to fluid continuity assessment, sample contamination assessment and digital sampling will also be discussed.

Acquiring reservoir fluid samples through formation testers is critical to asset evaluation in most oil and gas drilling operations. From the time this technology was introduced to the industry, the key challenges have been in planning the job, estimating contamination during operation, and obtaining clean fluid samples in the shortest time possible. The objective of this paper is to create a new data-driven model to proactively simulate the cleaning process in order to provide a practical job-planning tool that optimizes fluid sampling. After detailed analysis of formation pump-out cleaning behavior and oil-well sampling, a parametric study with nearly a hundred thousand scenarios was designed to model fluid behavior during sampling. The simulation scenario is a multi-component model with radial geometry, capable of handling complex reservoir rock, fluid composition, probe geometry, and sampling conditions. Compositional simulation output is then used to generate the comprehensive database of the fluid sampling and cleaning processes. The study is used to determine the sensitive parameters related to sampling and contamination. Full factorial experimental design was used to build nearly one hundred thousand scenarios with more than 10 relevant parameters. Outputs were analyzed through a variety of visualization and statistical techniques to understand cleaning behavior in different initial and operating conditions. One-factorial analysis and statistical tests, including analysis of variance (ANOVA), were used to determine the significance of the different parameters. The most influential parameters have been selected and used as input to the representative model in order to predict pumpout volume and corresponding contamination. In this work, multiple data-driven models such as Neural network, Random Forest, and Gradient Boosting are presented. Furthermore, multiple mathematical equations have been compared to fit the contamination trend, and methods of estimating their best fit parameters are presented. Blind testing has been performed to evaluate performance of the developed models, showing promising results. The workflow, database, and the developed models can be used to perform forward modeling of sampling jobs in different reservoirs, drilling muds, and operating conditions for both wireline and logging while drilling (LWD). This enables an effective and practical job-planning tool implementation, whereby a tool string can be optimized to reduce sampling time while improving the quality. The state-of-the-art workflow deployed in a commercial reservoir simulator combines physics, programming, statistical analysis, and machine learning techniques to tackle the challenging problem of sampling. The workflow and data can be used during operations with various wireline formation testing (WFT) and LWD testing tools to optimize cleanup and sampling of formation fluids. Simulations of different realizations of reservoir properties, drilling mud invasion profiles, and cleanup operations also helped develop a useful and diverse pumpout database.

In this paper a new method of performing a wireline large scale formation test is introduced. To measure reservoir properties a significant distance from the wellbore, drill stem testing (DST) tests are often employed. In addition to measuring reservoir dynamic properties, a DST provides information regarding reservoir geometry including the extent of the reservoir, upper and or lower boundaries of the reservoir, barriers to flow within the reservoir. The DST is considered the gold standard for dynamic parameters such as reservoir pressure, formation mobility/permeability, well bore skin factor, flow anisotropy, and the best estimate of production potential for the measured interval. Conceptually, a typical DST is simply a controlled limited production of formation fluids over the reservoir interval of interest. However, a full DST has become an operationally intensive and costly endeavor often lasting many days to weeks. Planning and executing a DST is costly requiring highly specialized equipment that is customized for a unique set of reservoir and operating conditions. One of the primary considerations is to insure the environmental compliant disposal of a considerable quantity of produced fluid. Due to the high cost of traditional DSTs, alternate methods of testing have been employed. Wireline formation testers capabilities have increased their pumping capacities and are used to perform a small scale mini-DST that has increasingly been employed as a substitute for full DSTs at a much lower cost. A mini-DST can provide measurements of the reservoir dynamic properties, albeit over a smaller depth interval and smaller radius of investigation. The mini-DST radius of investigation generally extends up to 100feet from the wellbore and over a vertical height of a few feet as opposed to the full DST which can extend thousands of feet from the wellbore and be extended over tens of feet covering an entire vertical producing interval. While a DST can accurately characterize an entire formation production interval's potential, the mini-DST can delineate the formation flow interval and determine the most productive layers, flow barriers and thief zones which are critical to optimizing the completion design. This new method combines a conventional wireline mini-DST and sampling procedure with an extended injection test in order to recover the reservoir flow interval geometry information and improve flow interval delineation. The mini-DST measures the local mobility of the formation, cleans the wellbore of mud filter cake and near well bore mud filtrate contamination, thus enabling the acquisition of a clean formation sample. When acquiring a formation sample the formation fluid properties can be determined with downhole sensors and a subsequent mini-DST can provide the in situ dynamic properties. A selected injection fluid can be used to reverse the process by flowing into the interval. Because the injection fluid would have known properties that are measured in controlled laboratory testing, the dynamic data results will be more definitive. For example, the viscosity will be known enabling the rock permeability determination, where traditionally only the mobility can be determined. In many cases the reservoir oil type is known and the injection fluid can be closely matched to improve the in situ dynamic data results. Aided by favorable backing pressure from the surface, and not limited by the fluid bubble point, the injection fluid may be pumped into the formation at a higher rate than the formation fluid can be withdrawn from the formation. This allows a greater sand face to reservoir pressure differential, yielding an improved pressure signal for evaluation. Furthermore, because fluid is injected, no environmental sensitive disposal is required, and the procedure is inherently safer for maintaining well integrity than a formation fluid withdraw. However, interpretation of the pressure rebound after the injection stops may require a reservoir simulation if the injection fluid property is significantly different from the in situ reservoir mobile fluid. This paper evaluates the new method based on detailed reservoir simulations and using available field equipment capabilities. These simulations include considerations of invasion and cleanup in a multiphase environment. In addition, a sensitivity study summarizes the testing effectiveness by varying the primary parameters such as permeability, anisotropy, skin, and formation barrier distances. From this work, conclusions are drawn comparing the new reverse injection DST method to traditional DST and wireline technologies.

Quality estimation of reservoir fluid compositions from optical sensor measurements (OPTs) is crucial for real-time downhole fluid analysis. Conventional workflow, which performs multiple single-analyte predictions with neural networks (NNs), often suffers the issue of mass balance in estimated outputs. In this study, single-analyte fluid characterization (SAFC) is compared with a novel multi-analyte fluid characterization (MAFC) method. The investigation aims to evaluate whether the new method can maximize the balance of the density concentrations of fluid compositions and provide self-consistent solutions to support early decision making on reservoir exploitation and production optimization. As an inversion problem, fluid characterization in this paper is accomplished in two stages using NNs. The first stage converts actual sensor measurements into synthetic optical responses. After the optical data transformation is completed, then fluid characterization at the second stage is applied using synthetic optical data inputs. The combination of optical data transformation and fluid characterization networks forms a concatenated optical computing network (COCN) for downhole fluid analysis. The performance evaluation is conducted on the calibration database first, followed by comprehensive testing assessment using simulation data and laboratory measurement data. Fluid characterization networks developed on a large database pertain to low uncertainty for both multi-analyte and single-analyte calibrations. SAFC networks allow for selecting analyte-specific network inputs and manipulating the network performance under its own connecting parameter space. However, the inherent data relationship and constraints among the fluid compositions and properties are not utilized to calibrate individual models. This limitation often leads to inconsistent compositional predictions on the new data and hence requires post-processing of output data from multiple single-analyte networks. MAFC networks, in comparison, have constraints of fluid compositions built into training outputs. By minimizing overall training error on all compositional outputs, MAFC networks structurally ensure the self-consistent predictions on analyte density concentrations. Nevertheless, sharing network parameters in the hidden layers necessitates the use of more complex MAFC network structures to improve overall prediction accuracy. The quality of optical data transformation, which affects all fluid compositional outputs with less flexibility in input selection, can present challenges during MAFC network application. Conventional optical data transformation networks calibrated on a small number of reference fluids are capable of supporting sensor-based fluid characterization but cannot justify the robust mapping for sensor-independent MAFC networks because of the limitation associated with sparse-data-based transformation model development. New transformation networks, which facilitate fluid analysis with generic optical inputs, are built through two-directional progressive calibration to improve data mapping. The resulting reverse and forward transformation networks can be optimized using measurement and simulation data and validated in real-time signal processing. Applying reverse and forward transformation networks alternatively, for example, can help determine the degree of matching between simulated and measured optical sensor data. Using the quality of matching as a performance index can also enhance uncertainty assessment of predictions from fluid characterization networks. It has been demonstrated that the novel transformation networks developed during this study provide more robust optical sensor data mapping and improve predictions for both MAFC and SAFC networks.

Robust downhole fluid analysis highly relies on quality measurements and data mapping from various optical sensors implemented into modern formation testers. The direct modeling used to determine a multivariate correlation between optical sensor responses and diverse fluid compositions or properties is often cost-prohibitive with sensor-based calibration. This paper presents a novel method based on concatenated optical computing neural networks (COCN), which link sensor-specific signal transformation to generic fluid characterization through validated data mapping. The COCN models are built separately in the in-house laboratory using optical data transformation networks and multi-analyte fluid characterization networks. To evaluate the uncertainty of sensor signal mapping, additional sensor data prediction networks, which exchange inputs and outputs of sensor data transformation networks to provide reverse data mapping, can be built to produce the simulated sensor responses. The actual sensor measurements are then compared to the simulated sensor responses to validate the optical signal transformation. The degree of matching can be used to identify issues associated with the quality of the sensor measurements and the range of calibration and testing data, and to select the transformation networks in ruggedizing predictions of fluid compositions and properties. This paper presents the method used and case studies to exemplify the application of the proposed approach for reliable fluid sample characterization using laboratory and field measurement data. Calibrating sensor-independent fluid predictive networks on a large database usually pertains to low uncertainty because the analyzed measurements can be collected from diverse reservoir fluid samples. The construction of data transformation networks, however, is only realistic by using a small number of reference fluids because of their high calibration cost, which conversely challenges the quality of data mapping with new field sensor measurements. In this study, sensor data transformation networks and sensor data prediction networks form two groups of mutually complementing models that can validate one another, making the quality of data mapping observable before applying fluid characterization models. The results of the case studies demonstrate that the consistency between the actual and simulated sensor responses is a reasonable performance index in the prediction of fluid compositions and properties. The laboratory and field examples also justified the importance of using simulation data appropriately to overcome the limitation of sensor measurement data in the calibration of transformation networks.

This paper presents a new optical sensor configuration using a multivariate optical computation (MOC) platform in order to enhance chemical analysis during formation tester logging operations. The platform allows access up to the mid-infrared (λ ~ 3.5 microns) optical region, which has previously not been accessible for in-situ real-time chemical measurements in a petroleum well environment. The new technique has been used in the field for the analysis of carbon dioxide and synthetic drilling fluid components such as olefins. MOC is a technique that uses an integrated computational sensor to perform an analog dot product regression calculation on spectroscopic data, optically, rather than by electronic digital means. Historically, a dot product regression applied to spectroscopic data requires both a spectrometer and a digital computer in order to perform a chemical analysis. MOC sensors require neither and because the key sensor component, the multivariate optical element (MOE), is a stable temperature robust solid-state element, the technique is well suited for downhole petroleum environments. A new dual-core configuration using two MOEs designed to work in parallel enhances the sensitivity of the measurement enabling a mid-infrared analysis. Spectroscopic measurements were performed on 32 base oils that were reconstituted to reservoir compositions over a wide temperature and pressure range up to 350°F and 20,000 psi for a total of 12 combinations for each base oil. Live gas compositions (i.e. reservoir conditions) were achieved by adding multiple methane, ethane, propane, and carbon dioxide charges to each base fluid. The reconstituted petroleum fluids were further mixed with olefin-based synthetic drilling fluid (SDF). This rigorous experimental design data therefore allowed for solid state MOEs to be designed to operate under the same reservoir conditions. Laboratory validation showed measurement accuracy of +/-0.43 wt% for a range of 0 to 16 wt% CO2 and +/-0.4% from 0 to 10 wt% SDF. A wireline formation tester optical section was modified with the MOC dual-core configuration to enable the mid infrared detection of both carbon dioxide and olefins. This formation tester was then deployed in five wells collecting seven samples from various locations. The downhole SDF and carbon dioxide measurements were subsequently found to be in good agreement with laboratory analysis with field results for valid pumpouts showing an accuracy of 0.5 wt% CO2 and 1.0 wt% olefins cross a range of 1.2 to 22 wt% CO2 and 1.4 to 9.7 wt% SDF. Carbon dioxide is an important component of petroleum whose presence and concentration affects completion options, surface facilities, and flow assurance, which thereby affects operational costs of petroleum production. Olefins are a primary component of synthetic drilling fluid (SDF), although other mid-infrared active components such as esters, ketones, alcohols, and amines also can be present. High concentrations of SDF in openhole formation tester samples lower the quality of laboratory phase behavior analysis and thereby force greater monetary risk in development of assets, especially when conducting reservoir production simulations. Therefore, it is important to monitor both components during formation tester sampling operations.

Phase behavior characterization (PVT) and geochemical compositional analysis of petroleum samples play a crucial role in the reservoir evaluation process to help determine producible reserves and the best production strategy. Openhole samples are the most valuable types of samples for PVT and geochemical analysis. Unfortunately, traditional openhole sampling methods are costly and limited to ten to twenty samples, thereby restricting the scope of characterization in a well section. This study summarizes a new microsampling technique for logging while drilling (LWD) and a corresponding wellsite technique to provide compositional interpretation, contamination assessment, reservoir fluid compositional grading, and reservoir compartmentalization assessment. This microscale approach allows fast analysis with a field or near-field deployment of the analytical tool, providing fast turnaround time for analysis. The results inform planning for wireline sample retrieval, if necessary. The microsampler used in the downhole tool is capable of collecting reservoir fluid in small quantities, suitable for compositional analysis. Because of its small size, the microsampler can gather multiple fluids at various reservoir depths, while PVT sampling requires larger volumes and has more constraints. However, when used in combination with conventional PVT-grade samples, the microsamples can provide significant chemical profiling. The quantity of 40 microliters (μl) provides the opportunity to collect many more samples than the conventional PVT sample size of 200 to 1,000 milliliters (ml). Additionally, 40 microliters provides more than enough of a sample for a complete chemical analysis using a liquid chromatograph or gas chromatograph coupled to either a mass spectrometer for biomarker analysis or a flame ionization detector for a complete assay. Isotope analysis is also possible. Recovery to surface of fluid samples collected at reservoir temperature and pressure allows for analysis with an automated gas chromatograph (GC) deployed in the field, providing reduced labor and rapid analysis. The unique injection chamber of the GC is designed with the injection port and valve configured to withstand pressure up to 5,000 psi, which is approximately five times higher than standard GC injection valves. This allows for injection of the microsample with a solvent carrier as a single-phase fluid so that analysis can provide composition and fluid properties, such as gas to oil ratio, without a flash. The GC has two detectors including a flame ionization detector (FID) for hydrocarbon components and thermal conductivity detector (TCD) for inorganic gas components, such as carbon dioxide, nitrogen, and hydrogen sulfide. The system can quantify hydrocarbon components from C1-C36 and perform contamination studies of oil samples with drilling fluids. This study provides a new technique for reservoir engineers to characterize a reservoir completely, without limit to the number of acquired samples. In combination with conventional PVT samples, it is possible to extrapolate the PVT properties to all pump-out stations, and conduct a complete geochemical profile of the reservoir.

The reservoir compartmentalization structure and fluid contacts of a field are essential for determining the value of a reservoir asset and provide the two primary purposes of pressure gradient determination. Several new straightforward data-analytical methods have been developed to extract pressure gradient information based on physical properties of the reservoir and meta-analysis of derived pressure gradient information. These methods can be used to provide near real-time feedback about the pressure measurements quality. This paper describes two distinct methods to determine reservoir compartmentalization structure and fluid contacts. The first method implements statistical evolution to rapidly identify pressure gradients. The second method transforms identified pressure measurements into a meta-analytical visual representation of pressure gradients vs. depth with additional input from measurement consistency. Both methods rely on the accurate removal of pressure outlier data, such as that attributable to supercharging. A new technique using expert knowledge of physical constraints was implemented for reliable outlier removal. The two methods then diverge in subsequent conditioning of the data, but re-converge in adapting an efficient fitting method to extract the desired information. Both methods provide reliable removal of pressure data that are not related to formation fluid densities, regardless of reservoir number, fluid number, or fluid type. To date, the removal procedure removes more than 95% of outliers and retains more than 90% of accurate pressure data. Both methods also return the correct number and types of fluids. Although pressure gradient estimation can vary by up to 50% for fluid zones of less than 50 ft, the estimation error of the pressure gradients is reduced to less than 3% for fluid zones greater than 100 ft. Furthermore, fluid breaks can be calculated to within 8 ft for the statistical evolution method and to within 30 ft using the visual method. Finally, although the statistical evolution method is markedly faster than the visual method, both techniques provide feedback within a few minutes. The methods discussed provide feedback about the necessity to retake or take more pressure data during formation-pressure surveys within minutes. This feedback eliminates the delay in reservoir property estimation and greatly increases the reliability and quality of pressure data obtained. The methods presented also use a new application of data meta-analysis to reduce processing time and increase reliability.

Mud filtrate invasion occurs in the immediate vicinity of the well as a result of the overbalance pressure of the mud column in the well. Oil-based muds (OBM), unlike water-based muds (WBM), are miscible with reservoir fluid, and OBM contamination alters the properties of the original formation fluid. The bubblepoint of contaminated fluid is usually lower than clean fluid. While fluid is pumped out of the formation, it becomes cleaner and the bubblepoint increases; the upper limit of the increase is the clean formation fluid. While increasing the pumping rate can shorten cleanup time, pumping below the bubblepoint can modify the fluid phase behavior and cause asphaltene content in the formation fluid to precipitate out and sensor data to become erratic and noisy. Therefore, it is important not to pump below the bubblepoint, knowing the clean fluid bubblepoint in real time provides a guideline for the field engineer. The purpose of fluid sampling is to collect a representative formation fluid—samples with an acceptably low contamination. The clean fluid bubblepoint provides a lower limit on pumping pressure, which helps ensure pumping does not go below the bubblepoint and the sample is in single phase. This paper describes how clean fluid compositions are determined from the asymptote of the principal component analysis (PCA) reconstructed scores and then used as input for the equation of state (EOS) program to compute fluid properties such as bubblepoint and gas/oil ratio (GOR). The optical spectral data from the optical fluid analyzer is first despiked, and outliers from the despiked data are removed using the robust ordinary least squares regression (ROLSR) method and robust PCA (RPCA). After removing outliers, clean fluid spectra data are reconstructed using asymptotic PCA scores and PCA loadings. Using a neural network model, clean fluid compositions are determined from reconstructed fluid spectral data, and fluid compositions are used as input for the EOS program to determine fluid properties. Results confirm that the clean fluid bubblepoint and GOR do not change significantly after a few tens of liters of fluid pumpout. Analysis of the first principal component (PC1) confirms that most of the variations occur during the first few tens of liters of pumpout, indicating the predicted clean fluid compositions and properties are somewhat stable. This approach can help determine the clean fluid properties, even while pumping before taking the sample, helping ensure a monophasic fluid sample. When pumpout accumulated volume reaches 40 to 50 L—within 15 to 20 min of pumping out contaminated fluid—clean fluid compositions and properties can be estimated and used to determine reservoir continuity. Additionally, knowing the clean reservoir GOR and API gravity can help determine the type of reservoir fluid in real time.

Hydrogen-sulfide gas is a toxic, colorless gas with a pungent odor that occurs naturally as a decomposition by-product. It is critical to monitor the concentration of hydrogen sulfide. Multivariate optical computing (MOC) is a method that can monitor analytes while minimizing responses to interferences. MOC is a technique by which an analogue calculation is performed entirely in the optical domain, which simplifies instrument design, prevents the drift of a calibration, and increases the strength and durability of spectroscopic instrumentation against physical perturbation when used for chemical detection and identification. This paper discusses the detection of hydrogen-sulfide gas in the ultraviolet (UV) spectral region in the presence of interfering gaseous species. A laboratory spectroscopic measurement system was set up to acquire the UV spectra of H2S and interference gas mixtures in high-pressure/high-temperature (HPHT) conditions. These spectra were used to guide the design and fabrication of a multivariate optical element (MOE), which has an expected measurement relative accuracy of 3.3% for H2S, with a concentration in the range of 0&ndash, 150 nmol/mL. An MOC validation system with the MOE was used to test three samples of H2S and mercaptans mixtures under various pressures, and the relative accuracy of H2S measurement was determined to be 8.05%.

Category: Ankle, Ankle Arthritis, Basic Sciences/Biologics, Hindfoot, Surgery Introduction/Purpose: Foot and ankle surgery with bone grafting relieves pain and improves function in patients with hind/midfoot conditions. Umbilical cord blood (UCB) derived allografts have gained recent prominence for their potential in tissue regeneration. UCB is enriched with cytokines which regulate autocrine and paracrine signaling. BioBurst Fluid (BBF) is a UCB derived cellular allograft carefully processed by the patent pending Progenokine™ technique to preserve the unique molecular heterogeneity of UCB. Clinical study is being conducted to determine the safety and efficacy of BBF administered in patients undergoing foot and ankle surgery (NCT03077256). Here we report our initial data from this ongoing study. In vitro biochemical characterization of BBF further established the osteogenic potential of this allograft and provided mechanistic link to its clinical efficiency. Methods: 57 patients undergoing surgery with concomitant BBF administration were enrolled in an IRB-approved study, the selection criteria being not to exclude anyone. Data obtained from 21 of the 57 enrolled patients completing their 6-month post- op is reported. The prospective registry recorded patient demographics, comorbidities, symptoms, fusion status, pain, pain medication use, and neurological status up to 6 months post-op. Surgical, immediate post-op, and follow-up complications were also recorded. Fusion was assessed at 3 and 6 months via anteroposterior and lateral x-rays. Pain and function were assessed with Visual Analogue Scale/VAS and modified Odom’s criteria. Neurological status was recorded as improved, maintained, or worse. Narcotic and NSAID use were rated as increased/same or decreased/discontinued. For in vitro characterization of BBF, standard cell-biology methods were employed using MSC as model system. Cytokine concentration in 30 random BBF lots was determined by Luminex multiplex assay. All data are analyzed using appropriate statistical tools. Results: No complications from administration of BBF were seen intra-operatively and during follow-up. Successful fusion (>50% incorporation) was achieved in 20/21 patients (95%) with 8 patients having fusion by 3 months. One non-union occurred in an HIV positive patient. VAS pain score improved clinically from pre-op at 3 months (-3.3, pConclusion: No adverse-event reports established the clinical safety of BBF. Extrapolation of this initial data suggests early and high rates of successful fusion and better than expected clinical outcomes in patients using BBF in foot and ankle procedures. These positive outcomes may be attributed to BBF’s molecular profile of anti-inflammatory cytokines which help in pain mitigation. Growth factors and chemokines present in BBF induce host MSC to participate in proliferation, recruitment, and osteogenic differentiation which contribute to bone regeneration and fusion.

Viscosity is driven by asphaltene content and is a key parameter in the development of heavy oil fields. Understanding fluid composition and temperature and pressure-induced changes in fluid viscosity is vital for an optimized production strategy and surface facility design. A recent field and laboratory study exemplifies the steps necessary to obtain the fit-for-purpose data from heavy oil samples. This paper presents the case study of a new downhole optical composition analysis sensor used during real-time downhole fluid analysis and sampling for the first time in a Kuwait heavy oil formation. The primary objectives of a sampling program are to confirm fluid indications on the openhole logs and collect crucial pressure/volume/temperature (PVT) samples. The downhole optical composition analysis sensor provides the information necessary to estimate a sample contamination level. It also indicates when the sample is sufficiently clean for PVT analysis. The samples should be acquired from the reservoir and maintained as single phase throughout transport to the laboratory. The pressure should be maintained higher than the asphaltene precipitation onset pressure and much higher than the bubblepoint. If the sample is not maintained higher than the asphaltene onset pressure, asphaltenes precipitate in the sample chamber and cannot be reconstituted as single phase in the laboratory. The new optical composition analyzer can also identify fluid stream components and their relative concentration in real time with laboratory-quality accuracy downhole. Near-infrared (NIR) sensors are most commonly used to identify fluid in the wireline formation tester (WFT). The sensors work well in light hydrocarbons. However, in heavy oil, the sensor performance degrades and fails to identify the contamination level accurately. The new multivariate optical computing (MOC) technique for downhole optical composition analysis overcomes this by performing a photometric detection with the entire relevant spectral range compared to spectroscopic analysis, which is only performed over a narrow band or sparse set of channels while traditional sensors are configured. The MOC sensor also recognizes in real time the chemical nature (optical fingerprint) of analytes (e.g., methane, ethane, propane, carbon dioxide, hydrogen sulfide, water, asphaltene, aromatics, and saturates) using all of the useful information in the optical spectrum. The real-time analyte chemical composition provided by the sensor is comparable to laboratory tests conducted on the collected PVT sample. Laboratory measurements on representative fluid samples from the correct locations early in the field development stage help develop an optimal field-development strategy. At the same time, sample integrity is maintained from the reservoir to the laboratory, which is vital. This paper discusses how the new optical compositional analysis sensor in combination with a high-resolution fluid identification sensor provides comprehensive and accurate downhole fluid composition in real time. This compares well with the laboratory-measured PVT analysis of heavy oil samples. The compositional analysis sensor optimizes pumpout time, thus helping obtain practically ideal contamination levels to begin the single-phase sampling process, which saves valuable rig time.

Imprint lithography has been shown to be an effective technique for replication of nano-scale features. Jet and Flash* Imprint Lithography (J-FIL*) involves the field-by-field deposition and exposure of a low viscosity resist deposited by jetting technology onto the substrate. The patterned mask is lowered into the fluid which then quickly flows into the relief patterns in the mask by capillary action. Following this filling step, the resist is crosslinked under UV radiation, and then the mask is removed, leaving a patterned resist on the substrate. Criteria specific to any lithographic process for the semiconductor industry include overlay, throughput and defectivity. The purpose of this paper is to describe the technology advancements made in the reduction of particle adders in an imprint tool and introduce the new mask replication tool that will enable the fabrication of replica masks with added residual image placement errors suitable for memory devices with half pitches smaller than 15nm. Hard particles on a wafer or mask create the possibility of creating a permanent defect on the mask that can impact device yield and mask life. By using material methods to reduce particle shedding and by introducing an air curtain system, test stand results demonstrate the potential for extending mask life to better than 1000 wafers. Additionally, a new replication tool, the FPA-1100 NR2 is introduced. Mask chuck flatness simulation results were also performed and demonstrate that residual image placement errors can be reduced to as little as 1nm.

Objectives: There has been a renewed interest in UCL repair in overhead athletes. This is largely due to greater understanding of UCL pathology, improvement in fixation technology and the extensive rehab required to return from UCL reconstruction. Initial data regarding UCL repair in overhead athletes was poor and therefore UCL repair was largely abandoned in favor of reconstruction. However, recent literature examining UCL repair with anchor only fixation demonstrated an excellent rate of return to play, reduced time to return to play and a low complication rate. Based on this promising data, we have developed a novel technique of UCL repair with internal brace augmentation that we have used in overhead throwing athletes. We performed a prospective study evaluating the outcomes of this procedure with respect to return to play, time to return to play, functional outcome score and complications. Methods: Overhead athletes undergoing UCL repair with internal brace augmentation were prospectively followed for a minimum of one year. Patients were carefully selected from those who would traditionally be considered for UCL reconstruction. Initially, patients were considered if they had an avulsion of the UCL with otherwise healthy UCL tissue and had a vested interest in shortened rehab. As the study progressed, interest in shortened rehab became a less stringent criteria. Demographic and operative data were collected at the time surgery. This data was compiled for both desciption and comparison between subgroups. Patients were then contacted 1 year postoperatively and assessed for return to play, time to return to play and KJOC scores. Complications were documented and patients having complications were detailed. Results: 66 overhead athletes underwent UCL repair with internal brace augmentation during the study period. 8 were lost to follow up, leaving 58 athletes included in the study. Average age at the time of surgery was 17.9 years old. There were 43 baseball pitchers, 8 baseball position players, 4 softball players, 2 football quaterbacks, and 1 javelin thrower. 96% (54/56) of those who desired to return to the same or higher level of competition were able to do so at an average time of 6.1 months (range 3.2-12 months). 65% of these were able to return in less than 6 months. Many of those who took longer than 6 months did so due to timing within the season. Average KJOC score was 90.2 at 1-year follow-up. 3 patients required return to the operating room, 2 of which were eventually able to return to their previous level of play. There was 1 late failure over 3 years from the index procedure. Comparative subgroup data is presented in table 1. Conclusion: UCL repair with internal brace augmentation is a viable option for overhead throwers with selected UCL pathology who wish to return to sport in a shorter time frame than allowed by traditional UCL reconstruction. Comparative Analysis of Subgroups. Time to return to N KJOC P-value play (Months) P-value Location of tear Distal 34 89.6 6.00 Proximal 24 90.6 P=0.71 6.19 P=0.74 Severity of tear Partial 35 89.5 6.14 Complete 23 91.4 P=0.51 6.08 P=0.86 Ulnar Nerve Transposition UNT performed 32 90.9 6.40 UNT not performed 26 89.4 P=0.17 5.75 P=0.16 Overall 58 90.2 6.13

Multivariate optical computing (MOC), an optical sensing technique for analog calculation, allows direct and robust measurement of chemical and physical properties of complex fluid samples in high-pressure/high-temperature (HP/HT) downhole environments. The core of this MOC technology is the integrated computational element (ICE), an optical element with a wavelength-dependent transmission spectrum designed to allow the detector to respond sensitively and specifically to the analytes of interest. A key differentiator of this technology is it uses all of the information present in the broadband optical spectrum to determine the proportion of the analyte present in a complex fluid mixture. The detection methodology is photometric in nature; therefore, this technology does not require a spectrometer to measure and record a spectrum or a computer to perform calculations on the recorded optical spectrum. The integrated computational element is a thin-film optical element with a specific optical response function designed for each analyte. The optical response function is achieved by fabricating alternating layers of high-index (a-Si) and low-index (SiO2) thin films onto a transparent substrate (BK7 glass) using traditional thin-film manufacturing processes (e.g., ion-assisted e-beam vacuum deposition). A proprietary software and process are used to control the thickness and material properties, including the optical constants of the materials during deposition to achieve the desired optical response function. The ion-assisted deposition is useful for controlling the densification of the film, stoichiometry, and material optical constants as well as to achieve high deposition growth rates and moisture-stable films. However, the ion-source can induce undesirable absorption in the film; and subsequently, modify the optical constants of the material during the ramp-up and stabilization period of the e-gun and ion-source, respectively. This paper characterizes the unwanted absorption in the a-Si thin-film using advanced thin-film metrology methods, including spectroscopic ellipsometry and Fourier transform infrared (FTIR) spectroscopy. The resulting analysis identifies a fundamental mechanism contributing to this absorption and a method for minimizing and accounting for the unwanted absorption in the thin-film such that the exact optical response function can be achieved.

Double-resonance spectroscopy, using collisional energy transfer to populate high-lying vibrational states, reveals the location of 27 previously undetected levels in the ground electronic state of HCN. Three laser-pumped overtones, (0,00,4), (0,00,5), and (1,00,5) provide the doorway through which to collisionally populate vibrational levels lying between 10330 and 17650 cm-1. This greatly increases the energy range over previous studies using collision-assisted spectroscopy and provides access to states which have internal energy above the predicted isomerization barrier. Levels populated by collisions from (0,00,4) and (0,00,5) are detected directly via A state fluorescence, while those from (1,00,5) are detected through resonant multiphoton dissociation resulting in CN (B→X) fluorescence. Although potentially, collision-assisted spectroscopy above the isomerization barrier could access HNC localized states, such states have not been identified in the present experiments.

Objectives: UCL reconstruction has become the preferred treatment for UCL injury in elite throwers desiring a return to throwing. Prior reports of UCL repair demonstrated poor results in professional pitchers, with rate of return to the same or higher level pitching between 0% and 63%. 1,3,6,9,11 However, in young athletes without chronic attritional UCL damage, recent data shows reliable and rapid return to sport with primary UCL repair.2,12,14 We previously introduced a novel UCL repair technique consisting of primary UCL repair, augmented with a spanning tape anchored at either end of the native ligament. Compared to UCL reconstruction, this construct demonstrated significantly greater resistance to gap formation, even at low cycles of valgus loading.8 The purpose of the current study was to compare the high-cycle fatigue mechanics of augmented UCL repair versus modified Jobe UCL reconstruction. We hypothesized that the repaired specimens would have less gap formation compared to the reconstruction group after 10, 100, and 500 cycles of valgus loading. Methods: Twenty fresh-frozen cadaveric upper extremities (10 matched pairs) were dissected to expose the anterior band of the UCL.3 The humeral and ulnar insertions of the UCL were identified and marked to measure ligament displacement.7 Each specimen was potted and mounted on a mechanical test frame.4,5,8,10,13 A 2 N-m valgus preload was applied to the native elbow followed by a 60 s hold and 500 cycles of valgus loading between 2 N-m and 10 N-m. A longitudinal split in the anterior band was created and the distal attachment of the sublime tubercle was released, simulating a distal avulsion tear of the UCL. Ten cycles were repeated in this torn state. Each pair was randomly separated into either a repair or a reconstruction group (Fig 1). Each specimen was then manually subjected to 100 cycles of flexion-extension range of motion to simulate early rehabilitation protocols. The specimens were again loaded for 500 cycles between 2 N-m and 10 N-m, followed by a ramp to failure at a rate of 1°/s. Torque and rotation were recorded in addition to gap measurements for the 10th, 100th, and 500th cycle of the intact and repair/reconstruction conditions. Gaps were measured optically8 as the change in distance of the two anatomical landmarks between the pre-cycling hold and the peak of the cycle of interest. A two-way ANOVA with repeated measures was used to detect overall differences in addition to post-hoc t-tests and Tukey’s HSD for between the two procedures and three conditions, respectively. Significance was set at p ≤ 0.05. Results: The repair group showed greater resistance to gapping compared to reconstruction after 10 (p=0.008), 100 (p=0.02), and 500 (p=0.004) cycles (Fig. 2) of valgus motion. There was no difference in the intact state; however, the repair group did exhibit a reduction (p=0.007) in gap in the torn state after 10 cycles. Conclusion: In this preliminary report, UCL repair using internal bracing is more resistant to gap formation under fatigue loading than the gold standard reconstruction technique. The time-zero failure properties of this repair technique are on par with those of traditional reconstruction, although similar differences also seen in the torn state at early cycles may act as a confounding factor. In young throwers with insertional UCL injuries, our UCL repair technique may provide a suitable alternative to reconstruction with similar biomechanical properties and faster return to sport.

An instrument is presented that is capable of measuring the optical spectrum (long-wave ultraviolet through short-wave mid-infrared) of fluids under a range of temperature and pressure conditions from ambient pressure up to 138 MPa (20 000 psi) and 422 K (300 °F) using ∼5 ml of fluid. Temperature, pressure, and density are measured in situ in real-time, and composition is varied by adding volatile and nonvolatile components. The stability and accuracy of the conditions are reported for pure ethane, and the effects of temperature and pressure on characteristic regions of the optical spectrum of ethane are illustrated after correction for temperature and pressure effects on the optical cell path length, as well as normalization to the measured density. Molar absorption coefficients and integrated molar absorption coefficients for several vibrational combination bands are presented.

Optical fluid analyzers have been used in wireline formation tests for real-time downhole fluid analysis during pumpout tests for over a decade. Based on conventional optical spectroscopic methods, they separate broadband light into its constituent wavelengths via notch filters or multichannel grating spectrometers. A few narrow wavelength constituents are then detected and mathematically recombined to yield an answer product. Complex hydrocarbon fluids have many overlapping spectra and are optically active over a wide range of optical wavelengths. Consequently, accurate analyte detection in hydrocarbon fluids generally requires analysis of a large number of wavelengths over a large spectral region. The performance and range of detectable analytes of conventional optical fluid analyzers is band-limited. Of all available spectra from visible to near- and mid-infrared, only a small fraction of spectral data is used. In addition, the splitting of the optical beam into its wavelength constituents typically decreases signal-to-noise ratios (SNR) by orders of magnitude thereby limiting the accuracy, sensitivity, and viable ranges of the answer product. A new downhole optical sensor platform has been developed for downhole in-situ fluid analysis based on multivariate optical computing (MOC) technology. Historically developed for other markets, MOC is a well-established tool that combines chemometrics and pattern recognition with the power of optical computing. The heart of this new optical sensor platform is an optical component called the ICE CORE™ integrated computational element. The ICE Core sensor is analogous to the processing chip of a PC and performs calculations literally at the speed of light within the multivariate optical computer. Each ICE Core special multilayer optical element is encoded with a pre-designed multivariate regression vector specific to an analyte or property of interest. These optical elements are typically very broadband and may have a response that extends from 400 nm to 5000 nm. The wide bandwidth of these optical elements combined with their intrinsic, high etendue SNR advantage enables laboratory-grade optical analyses downhole. The compact and passive nature of the ICE Core sensors results in high reliability. A multivariate optical computer may consist of many different ICE Core sensors designed to detect many different analytes or properties. The downhole optical sensor platform in this study can have 20 (or more) different ICE Core sensors per MOC. This platform has been under field trial qualification for over a year using a step-by-step process with methane (C1) ICE Core sensors as the primary validation analyte. In this paper, the results of three different downhole pumpout field trials are presented. After reviewing the fundamental principles of MOC and ICE Core technology, the field trial validation process is described. Results showing downhole ICE Core measured methane analyte concentrations vs. time are presented and compared with other downhole sensor data. ICE Core measured concentrations are also compared with independent laboratory test results. The results demonstrate the downhole viability of the optical platform and the sensitivity associated with the ICE Core detection method.

Significant advances have been made in formation testing since the introduction of wireline pumpout testers (WLPT), particularly with respect to downhole fluid compositional measurements. Optical sensors and the use of spectroscopic methods have been developed to improve sample quality and minimize sampling time in downhole environments. As a laboratory technique, spectroscopy is a ubiquitous and powerful technology that has been used worldwide for decades to measure the physical and chemical properties of many materials, including petroleum, geological, and hydrological samples. However, laboratory-grade, high-resolution spectrometers are incompatible with the hostile environments encountered downhole, at wellheads, and on pipelines. Only limited resolution techniques are available for the rugged conditions of the oil field. This paper introduces a new optical technology that can provide high-resolution, laboratory-quality analyses in harsh oilfield environments. A new technology for optical sensing, multivariate optical computing (MOC), has been developed and is a non-spectroscopic technique. This new sensing method uses an integrated computation element (ICE) to combine the power and accuracy of high-resolution, laboratory-quality spectrometers with the ruggedness and simplicity of photometers. Many modern sensors typically merge the sensor with the electronics on an integrated computing chip to perform complex computations, resulting in an elegant yet simplistic design. Now, optical sensing using ICE features an analogue optical computation device to provide a direct, simple, and powerful mathematical computation on the optical information, completely within the optical domain. Because the entire optical range of interest is used without dispersing the light spectrum, the measurements are obtained instantly and rival laboratory-quality results. A proof of concept MOC with ICE has been demonstrated, logging more than 7,000 hours, in nearly continuous use for 14 months. Oils with gravities ranging from 14 to 65°API have been measured in downhole environments that range from 3,000 to 20,000 psi, and from 150 to 350°F. Hydrocarbon composition measurements, including saturates, aromatics, resins, asphaltenes, methane, and ethane, have been demonstrated using the MOC configuration. As compositional calculations therein, GOR and density are validated to within 14 scf/bbl and 1%, respectively. The paper discusses the details of the new ICE-based sensor and describes its adaptations to downhole applications.

The Jet and Flash Imprint Lithography (J-FILTM) process uses drop dispensing of UV curable resists to assist high resolution patterning for subsequent dry etch pattern transfer. The technology is actively being used to develop solutions for memory markets including Flash memory and patterned media for hard disk drives. It is anticipated that the lifetime of a single template (for patterned media) or mask (for semiconductor) will be on the order of 10 4 - 10 5 imprints. This suggests that tens of thousands of templates/masks will be required to satisfy the needs of a manufacturing environment. Electron-beam patterning is too slow to feasibly deliver these volumes, but instead can provide a high quality "master" mask which can be replicated many times with an imprint lithography tool. This strategy has the capability to produce the required supply of "working" templates/masks. In this paper, we review the development of the mask form factor, imprint replication tools and the semiconductor mask replication process. A Perfecta TM MR5000 mask replication tool has been developed specifically to pattern replica masks from an ebeam written master. Performance results, including image placement, critical dimension uniformity, and pattern transfer are covered in detail.

The Jet and Flash Imprint Lithography (J-FIL TM ) process uses drop dispensing of UV curable resists to assist high resolution patterning for subsequent dry etch pattern transfer. The technology is actively being used to develop solutions for memory markets including Flash memory and patterned media for hard disk drives. It is anticipated that the lifetime of a single template (for patterned media) or mask (for semiconductor) will be on the order of 10 4 - 10 5 imprints. This suggests that tens of thousands of templates/masks will be required to satisfy the needs of a manufacturing environment. Electron-beam patterning is too slow to feasibly deliver these volumes, but instead can provide a high quality "master" mask which can be replicated many times with an imprint lithography tool. This strategy has the capability to produce the required supply of "working" templates/masks. In this paper, we review the development of the mask form factor, imprint replication tools and processes specifically for semiconductor applications. The requirements needed for semiconductors dictate the need for a well defined form factor for both master and replica masks which is also compatible with the existing mask infrastructure established for the 6025 semi standard, 6" x 6" x 0.25" photomasks. Complying with this standard provides the necessary tooling needed for mask fabrication processes, cleaning, metrology, and inspection. The replica form factor has additional features specific to imprinting such as a pre-patterned mesa. A Perfecta TM MR5000 mask replication tool has been developed specifically to pattern replica masks from an e-beam written master. The system specifications include a throughput of four replicas per hour with an added image placement component of 5nm, 3sigma and a critical dimension uniformity error of less than 1nm, 3sigma. A new process has been developed to fabricate replicas with high contrast alignment marks so that designs for imprint can fit within current device layouts and maximize the usable printed area on the wafer. Initial performance results of this marks are comparable to the baseline fused silica align marks.

Collecting representative, single-phase retrograde gas samples from heterogeneous fractured carbonate formations is challenging, especially for cases in which the reservoir pressure narrowly exceeds the dewpoint. Conventional wireline probe/packer assemblies are undesirable in this situation because their small diameter probes increase the pressure drawdown, compared to other available intake configurations. Furthermore, the likelihood of establishing hydraulic communication with an open fracture or vug is low with a ½-in. diameter probe, compared to setting straddle packers spanning a 1-m formation interval. The straddle packer intake geometry reduces the drawdown pressure required to establish flow, thus maintaining the flowing pressure above the dewpoint and preventing the onset of unwanted condensation. Inflatable straddle packers can be run with pump-out test tools, but they have temperature, pressure, and operational limitations. The new Oval Pad* design, an elongated oval-shaped probe/pad assembly, possesses many of the advantages of dual packers without their limitations. Like a straddle packer, the Oval Pad tool is effective when testing thinly laminated and tight formations as well as fractured or vuggy carbonates. The oval shape enables the pad to encompass a significant vertical length of the borehole while establishing a pressure seal with the formation. A retrograde gas reservoir is contained within the vuggy carbonates in the Jambi Merang area of South Sumatra. Here the reservoir pressure narrowly exceeds the dewpoint. Pressure must be maintained above the dewpoint during sampling operations to prevent unwanted phase separation. The RDT pump-out tester was fitted with Oval Pad and nitrogen-charged sample bottles to collect single-phase samples and to keep the phase intact until PVT properties can be analyzed in the laboratory. These samples were necessary to determine laboratory PVT properties and to define a production strategy. This paper presents the details and challenges of the successful collection of single-phase samples in this environment.

Objectives: High level baseball pitchers are prone to shoulder and elbow injuries, resulting in significant morbidity and missed time from sport. This is the first study to use both subjective and objective preseason evaluations of baseball pitchers to predict injuries that occur in-season. We hypothesize that athletes reporting unfavorable scores on subjective questionnaires, and athletes falling outside the established pre-season normative values for objective data are more likely to develop injuries in season. Methods: Over three collegiate baseball seasons from 2011 through 2013, a cohort of collegiate Division I baseball pitchers underwent both objective and subjective evaluation prior to the start of the fall collegiate season. Preseason analysis included range of motion (ROM) in 5 planes, upper extremity manual muscle testing (MMT), Functional Movement Screen (FMS) assessment, a Kerlan-Jobe Orthopaedic Clinic (KJOC) Overhead Athlete Shoulder and Elbow score, an Upper Extremity Patient History (UEPH) questionnaire, and a Modified American Shoulder Elbow Score (MASES) questionnaire. This cohort was monitored over the course of the subsequent season for the development of injury and missed game time. A descriptive analysis for each questionnaire and all objective variables was performed. Univariate and multivariate regression models were used to explore potential risk factors for upper extremity (UE) injuries. Scatter plots, Spearman's correlation coefficients, and corresponding p-values were used to examine the relationship between subjective responses, objective physical parameters, and injury days missed. Results: Forty-two athletes participated in the study over three consecutive collegiate baseball seasons. Our preseason normative values for ROM, MMT, and the KJOC questionnaire are shown in Tables 1, 2, and 3. The mean KJOC score for our cohort was 86.93/100 (SD 12.49), and the mean MASES score was 88.4/100 (SD 21.7). The mean FMS score in our cohort was 15/21 (SD 3). Injury data for our cohort are shown in Table 4. After three full seasons, a lower KJOC score significantly correlated with injury days missed (Spearman's rho = 0.63, P-value 0.0122). Through the first two seasons, pitchers with a 1% higher UE rating on the UEPH questionnaire had 9.5% lower odds of developing injury during the season (OR 0.9149, 95% CI 0.8525-0.9819, P Value 0.014). Pitchers reporting every 1 unit higher of subjective instability had 61.27% higher odds of developing an UE injury (OR 0.6127, 95% CI 1.1044-2.3549, P value 0.013). However, by the end of the third season, and after adjusting for the use of pain medication, these variables failed to reach significance in our multiple regression analysis. Dominant shoulder TAM, rotator cuff strength, and glenohumeral internal rotation deficit (GIRD) were not predictive of injury in our cohort; although having over 5 degrees of difference in TAM vs the non-dominant shoulder approached significance (P-value 0.0598). Conclusion: This is the first study to demonstrate predictive value of subjective questionnaires. The KJOC Overhead Athlete Shoulder and Elbow Score can be used as part of the standardized preseason athlete evaluation to target pitchers at risk for developing injuries in-season. Objective parameters - notably TAM, GIRD, and rotator cuff strength - were not predictive of injuries in our cohort, which contradicts prior reports. To our knowledge, normative FMS data has not yet been established in baseball pitchers.

Due to their small dimensions when used for visible light, the patterning of photonic crystals has only been possible with costly electron beam lithography and low throughput R&D and pilot production grade imprint lithography. This paper will focus on results from a high throughput imprint tool capable of processing over 20 wafers per hour on 50- 100mm sapphire, GaAs, SiC, Ge and metal substrates. An overview of the process used as well as the results of patterning photonic crystal patterns on sapphire wafers and etching them into a SiO2 hard mask will be presented. Finally an analysis of the cost of ownership which currently stands at ~ $20/wf (

SFIL/R patterning has been used to pattern 100 nm photonic crystal structures on substrates commonly used in the photonics industry. A lithography process is demonstrated through hard mask patterning including on die patterned wafers.

The Step and Flash Imprint Lithography (S-FILTM) process uses field-to-field drop dispensing of UV curable liquids for step and repeat patterning for applications where high-resolution mix-and-match overlay is desired. Several applications, including patterned media, photonic crystals and wire grid polarizers, are better served by a patterning process that prints the full wafer since alignment requirements are not so stringent. In this paper, a methodology for creating high resolution thin templates for full wafer (or disk) imprinting is described. The methods have been applied toward the imprinting of both patterned media and photonic crystal devices using a large area printing tool developed around the S-FIL process. Techniques for further enhancing the pattern density as well as a method for addressing feature image placement are described. Finally, a process for replicating a Master Template is discussed in detail.