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Frequency stability is an important factor for the safety and stability of the power system operation. In a traditional power system, the operation stability is ensured by the inertia response, primary frequency modulation, and secondary frequency modulation. In recent years, in order to achieve the goal of carbon neutralization and carbon peaking, China has made great efforts in new energy development. With large-scale new energy connected to the power grid, the proportion of traditional conventional synchronous units has gradually declined. At the same time, a large number of power electronic devices have been used in the power grid, which led to the capability decline of the inertia response and primary frequency modulation. For example, the East China Power Grid has experienced a sharp frequency drop in such an environment. In order to solve the above problems, the operation principle and control mode of various new energy resources are analyzed in this paper. Moreover, the process and principle of power grid frequency response are studied and the evaluation index of frequency response capability is proposed. The research results can quantitatively evaluate the system inertia response and primary frequency modulation level and provides a judgment tool for dispatching operators and system planners.

During waterflooding, formation fines migration is a recognized reason for well injectivity and productivity reduction in sandstone reservoirs. Permeability decrease due to fines migration is one of the major issues in the application of low salinity enhanced oil recovery techniques. Recently, nanoparticles injection is found to reduce the fines release in sandstone cores through adsorption on the pore surface. In this research, a numerical model is developed to explore the coupling processes of nanoparticle transport, fine attachment and release, aqueous species reactive transport, and multiphase flow. Components including oil, water, salt, fine particles and nanoparticles are considered in this model. Both fluid dynamics and physical interactions are integrated in the coupled simulation approach. The nanoparticles exist in aqueous phase during injection, and can be attached to the solid surfaces to decrease surface energy. The formation fines can be suspended in aqueous phase, or retained by pore throats that decrease the permeability. The fines retention is modeled as a dynamic process where the retention rate is a function of salinity, nanoparticle adsorption, and flow velocity. The wettability alteration due to nanoparticle and low salinity is also included. A compositional simulator is developed based on implicit pressure explicit composition to include the detailed mathematical description of the complex processes. This paper provides detailed procedures of building a nanoparticle and fines transport and interaction model. To calibrate the diffusion/dispersion and adsorption isotherm constants, lab core flow experiments with nanoparticle injection are simulated. The fines migration experiments are simulated with and without nanoparticle injection at varying salinity. Simulation results demonstrate that the nanoparticle injection can effectively reduce the fine release and prevent permeability decrease at different salinity. In addition, the heterogeneous field scale simulation was performed. The oil recoveries with and without nanoparticle injection are compared for low salinity water injection. The simulation results indicate that using nanoparticles in low salinity waterflooding can improve oil recovery with mitigated formation damage. This work demonstrates a compositional model that can be used to simulate nanoparticle technology enhancing waterflooding performance. It is believed to be the first numerical model that explicitly includes the nanoparticle transport and its effect on fines migration. This paper will improve the understanding of geochemical conditions and spatial distribution of fines retention and whether the sweep efficiency will be improved.

One reason for observed reductions in the conductivity of hydraulic fractures is failure of the proppant pack. Proppant deformation, crushing, or embedment can decrease the fracture width and conductivity. In this paper, the continuity and momentum balance equations were fully coupled to simulate the transient phenomena involving fluid flow through a deformable porous proppant pack. Porous media displacement, water pressure, and gas pressure were derived as primary unknowns. The governing equation was discretized using the finite element method and solved numerically. In this model, the proppant pack and formation rocks were treated as two different types of continuous porous media (Biot type). Proppant deformation, crushing, and embedment could be identified through the geomechanical model, while the damage effects on gas/oil production would be studied through the fluid-flow model. Analysis of proppant deformation and crushing was based on the proppant pack stress–strain behavior. The displacement of the fracture-formation interface represented both the deformation of proppant and rock solids around fracture surface. Mohr–Coulomb failure was used as the criterion for proppant crushing. Effects of proppant damage were evaluated on proppant pack porosity and permeability. The model can be applied generally in hydraulically fractured reservoirs with proper inputs. In this paper, we used a fractured tight sand gas reservoir as a study case. The pressure distribution as well as proppant pack deformation are illustrated in the paper. Proppant pack mechanical behavior was found to be sensitive to the fluid flow pressure. Proppant near the wellbore has a higher likelihood of being crushed.

The well testing technique is an important tool in estimating well and reservoir characteristics, such as permeability, skin factor and so on. For a long time, researchers have been searching for automatic well testing interpretation tools, but the results are disappointing. This paper proposes using convolutional neural network (CNN) as an automatic well test interpretation approach for infinite acting reservoirs. The CNN takes pressure change and pressure derivative data of the log-log plot for inputs. The wellbore storage coefficient, skin factor and reservoir permeability are redefined into a dimensionless group C D e 2 S as the output of the CNN. In this method, the best trained CNN structure is obtained by minimizing mean square error (MSE) and mean relative error (MRE). This new method is tested for its effectiveness and accuracy in Daqing oil field, China. It demonstrates that, for wells in infinite reservoir, CNN could be an effective automatic well test interpretation technique. CNN also shows the potential for more complicated scenarios.

Given the expense of drilling in resource development, explore the optimal drilling operations, especially improve the rate of penetration (ROP), has become increasingly important. The prediction of ROP is challenging due to the complex bit and rock interactions. Several experience based models have attempted to predict ROP, but few of them can have excellent estimations. In this paper, a new ROP prediction methodology is developed using machine learning techniques. The booming computation capacity and large volume of data provide a new way to solve the problems. In this paper, wells from southern China have been used to demonstrate our approach. Well logging, mud logging data, geological information, daily well reports, and many other data have been included for the model development. Parameters which have been previously considered irrelative to ROP calculation show their impacts in the model. The machine learning approaches bring new insights into the ROP prediction. Comparing with the conventional approach, our method consider drilling as a continuous procession. ROP at current time relates to the drilling rate in previous time step. In our case, the model improves ROP estimation accuracy. In addition, engineers can use this tool to arrange better drilling plans during operation. Dive deep into the data, the acceleration and deceleration of ROP showed close relationship to WOB and mud properties, improve the mud rheology and operation strategies can keep the ROP in a optimal range which may enhance the drilling efficiency. With the assistance of machine learning techniques, a new method of ROP prediction has been developed. Comparing with the conventional approaches, this method considers more parameters and improves accuracy. Factors that may enhance the drilling bit performances were also explored. This new data driven method can be beneficial for drilling efficiency.

Sustainable well integrity, for the life time of the well and long after abandonment, has always been a target for operators. However, unplanned stresses on the set-cement can cause severe damages to the cement sheath and may ultimately result in its failure. For that reason, a new generation of cementing system with optimized mechanical properties and self-sealing capabilities were designed. The improved elastic constants and tensile strength value of the system make it more resistant to downhole stresses while the self-sealing feature provides an additional layer of assurance for long-term zonal isolation. The cement sheath’s ability to sustain stresses was confirmed using analytical and Finite Element Analysis (FEA) simulators. The mechanical properties and the expansion ratio were tested over several days, and the sealing ability was verified using a novel HPHT multi-function test cell simulating the well’s downhole conditions. The system was successfully deployed in cementing a challenging gas-injector well with a dual hole size in the UAE. Novel fluid displacement software was used to assess effective laminar flow as the industry-recommended turbulent fluid flow was not achievable. The injector well is expected to be under an alternating pressure of 5,500 psi with two sets of perforations set 47 ft. apart. The cement placement operation was carried out successfully and a Cement Bond Log (CBL) run was conducted after 48 hours verifying good zonal isolation over the entire interval. An injectivity test was performed on the two perforated zones. No fluid communication was observed, eliminating the need for any cement remediation. The successful implementation of the fit-for-purpose self-sealing resilient cement system from the slurry design and lab testing through the cement placement is described. Modelling simulation of the stress analysis, ECD and fluid displacement will be also shared. The review of this case history will provide useful lessons learned for successful cementing of critical wells.

During the fracturing treatment, fracturing fluid is pumped to generate fractures and then followed with a large amount of proppant to provide enough conductivity for reservoir fluid to flow to the wellbore. The ultimate proppant distribution in the fracture system directly impacts well productivity and production decline rate. However, it is very challenging to predict how far proppants can go and where they will settle because of the complexity of the fracture system. Previous modeling and experimental studies were usually based on simple proppant settling velocity models and limited only to planar fracture cases. In a recent numerical study, proppant transport in different complex fracture geometries was modeled. However, the fracture walls in the model were considered to be perfectly smooth. In this study, proppant transport in complex fracture geometries with different wall roughnesses was investigated using computational fluid dynamics (CFD) model, in which the interaction between proppant particles, the carrying fluid phase, and the rough fracture wall was fully coupled. A planar fracture case with smooth fracture wall was first investigated using a CFD model and benchmarked with results from commercial software. The CFD models were then used to simulate the proppant transport in T-junction and crossing-junction scenarios with different fracture wall roughnesses, which are often seen in unconventional reservoir fracture systems. The results from the CFD models indicate that proppant transport within complex fracture geometries is significantly affected by fracture wall roughness. Rough fracture wall can exert resistant drag force to proppant particles and carrying fluids and hence influence the proppant transport behavior and particle distribution. It is found rough fracture wall decreases both proppant horizontal transport speed and vertical settling speed which can lead to a better vertical coverage of proppant particles in the fracture. However, more pumping energy and time are required to transport the proppant particles to the same fracture length with rough fracture surfaces compared to smooth fracture surfaces. Studies on proppant density show light weight proppant has a better vertical distribution in fractures with rough walls due to more pronounced drag force effect. With high viscous carrying fluids, proppant in both smooth and rough fractures can transport further at the same transport time. Proppant transport models developed in this work fully incorporate the interaction between proppant particles, carrying fluid dynamics, and rough fracture surfaces. This study extends the current understanding of proppant distribution in complex fracture geometries and helps optimize hydraulic fracturing design to improve unconventional well production performance.

For the heavy oil fields of the Orinoco oil belt in Venezuela, a new cementing concept was successfully applied to maintain zonal isolation during long term exposure to temperatures up to 1,202°F (650 °C) in a process called in-situ combustion. These unconventional wells are often associated with weak and unconsolidated formations complicating proper cement placement and the resulting cement sheath must withstand extreme stresses due to the temperature and pressure cycles during the in-situ combustion process. During a comprehensive lab study API cement based slurries were engineered with high temperature stable aluminosilicate fibers. The corresponding cement specimens were cured and then exposed in a furnace with temperature cycles up to 1,202°F (650 °C) simulating the anticipated wellbore changes. Mechanical properties and permeabilities of these cementing systems were used in a computerized cement-sheath model to evaluate potential failures from stresses during the in-situ combustion process. The cementing systems containing 50% of the aluminosilicate fiber were suitable to withstand thermal degradation without any visual cracks. The computerized cement-sheath simulations indicated that stresses induced by prompt pressure and temperature changes during the heat cycles are not causing failures for the lead cement sheath which was critical to provide zonal isolation above the combustion zone. The biggest improvement of this thermal shock resistant cementing system towards the corresponding cementing systems not containing the aluminosilicate fibers was the significantly reduced Young's modulus by around -20%, while the tensile strength increased by at least +60% resulting in a desired resilient cement sheath. The actual cement jobs in the field were successfully executed as planned without any losses or incidents. So far, no well integrity issues have been observed since the well was cemented in March 2012 with the following combustion process. The thermal shock resistant cementing system, based on API cement, has advantageous towards refractory cements (such as high alumina cements) due to economics, ready availability, but in particular because it performs reliably by adjusting the slurry performance with common chemical admixtures and being flexible in design simplifying operations while contributing to a high-quality job.

The key in unlocking unconventional reserves is to create massive fracture surface area. During the fracturing treatment, a huge volume of fracturing fluid is pumped to generate fractures and then followed with a large amount of proppant to provide enough conductivity for reservoir fluid to flow to the wellbore. The ultimate proppant distribution in the fracture system directly impacts well productivity and production decline rate. However, it is very challenging to predict how far proppants can go and where they will settle because of the complexity of the fracture system. Therefore, accurate modeling of proppant transport inside the fracture system is critical to enable stimulation optimization. Previous modeling and experimental studies were usually based on simple proppant settling velocity models and limited only to planar fracture cases. To accurately evaluate propped complex fracture systems, which are more common in unconventional reservoirs, advanced proppant transport models are required. In this paper, proppant transport in various fracture geometries is investigated using computational fluid dynamics (CFD) models, in which the interaction between proppant particles and the carrying fluid phase is fully coupled to track proppant movement in the fractures. The planar fracture case is first investigated using a CFD model and benchmarked with results from commercial software. The CFD models are then used to simulate the proppant transport in T-junction and crossing-junction scenarios, which are often seen in unconventional reservoir fracture systems. Parametrical studies are also conducted to better understand how proppant transport is affected by fracture fluid viscosity, proppant density, and fluid injection rates. The results from the proposed CFD models indicate that proppant transport within complex fracture geometries is significantly affected by fracture fluid dynamics and proppant properties. At fracture junctions, turbulent flow regime will develop, which helps proppant propagate to natural fractures. According to the parametrical studies, higher injection rate and light-weight proppant are beneficial in transporting proppant through fracture junctions to reach further in both hydraulic fractures and natural fractures. Proppant transport models developed in this work fully incorporate the interaction between proppant particles and carrying fluid dynamics. This study extends the current understanding of proppant movement in complex fracture geometries and helps optimize hydraulic fracturing design to improve unconventional well production performance.

During the life time of a production well, sometimes it is inevitable that remediation methods have to be adopted for different reasons. Hydraulic fracturing is one of the common ways to boost production by either reopening existing fractures or creating new fractures. Considering the large number of unconventional wells that have experienced sharp production declines and the current tight budget for drilling new wells, refracturing will certainly become an important technology worthy of more investigation. This paper reviews the production and completion data for a number of wells that have been re-stimulated by hydraulic fracturing since 2011. Wells with enough production data were selected to evaluate their production responses by comparing both the cumulative production in a fixed period of time before and after the re-stimulation and by evaluating incremental production increase normalized by amount of proppant used to restimulate the well. Wells involved in the study had been producing from various formations for different periods of time before restimulation. In addition to the analysis above, this study went a step further by attempting to understand the reasons behind inconsistent results after refracturing: high performance of some wells and the failure of the others to meet production expectations. Two re-completion effectiveness indexes are defined in the paper based on production performance before and after restimulation and on re-completion job size. Overall, the study shows mixed results. Although some formations demonstrated much more favorable response than others, it was also possible for wells producing from the same formation to have extremely different responses to the restimulation. Candidates for restimulation should be evaluated carefully, to include their level of depletion, the petrophysical and geomechanical properties of the rock, and previous well completion and stimulation. These data and measurements are required to engineer an appropriate refracturing or recompletion design. The study also shows very promising results from refracturing some long-producing conventional wells, which indicate opportunities to rejuvenate old wells with hydraulic fracturing. This study provides an overview of the lessons learned from examination of a limited data set of hydraulic fracturing restimulations done in the past five years.

Waterflooding is an established conventional method to improve oil recovery. When water flows into pores in a rock formation occupied by hydrocarbons, clays and other formation fines are released and flow with the injection water. Left unaddressed, the released formation particles can accumulate and plug the pore throats in the flow channels, which cause higher water injection pressure, lower water sweep-efficiency and lower oil recovery. Chemical additives in the injection water to stabilize formation clays and fine particles during waterflooding operations are partially helpful. Several major operators established a goal for 70% oil recovery, motivating the research of higher performing waterflooding formulations. As the nanoparticle-loaded water drives hydrocarbons toward the producers, the nanoparticles fixate formation fines at their sources in the water flow channels, resulting in fewer fines accumulating at the near-wellbore region of the producers (causing less choking to the production of hydrocarbons) and resulting in water-sweep-efficiency increases. This paper presents the results with and without using nanoparticles in simulated waterfloodings. In addition to cleaner water effluent, lower pressure drop occurs across the porous media containing nanoparticles under the same flow rate of 5%KCl and the same porous media compositions of sand and simulated formation fines. Full reservoir simulation details the benefits of coupling the nanoparticles and waterflooding in high fines-containing reservoirs with various reservoir properties. This paper presents the use of select nanoparticles in waterflooding to significantly improve oil recovery in reservoirs susceptible to formation fines migration. The research shows the unique ability of select nanoparticles in stabilizing formation clays and fines in waterflooding operations. The lab results demonstrate a much higher performance of the new nanoparticle-blended waterflooding than the currently used technology of stabilizers for formation clays and fine particles. Lab tests, even visually, show a clear improvement of the water-effluent quality (less fines) when the nanoparticle-blended waterflooding is pushed through the lab-constructed permeable media. The simulation resulted in 37% more production than regular waterflooding in a higher permeability reservoir case and 95% greater production in a lower permeability reservoir scenario. The paper includes the scientific principle behind the nanoparticle functioning, detailed lab results and the reservoir simulations.

Gel damage has been identified as the most severe damage effect on gel-fractured well productivity. The reduced effective fracture length and fracture conductivity can significantly decrease the initial production rate and the ultimate recovery, especially for tight reservoirs. In this paper, we conduct numerical studies on fracture cleanup effects, and explore procedures for improving post-fracture production. To effectively simulate fracturing fluid rheology and transportation, a dual continuum method is employed in our model. Gel residue inside the fractures is determined based on gel and breaker reaction dynamics from experimental data. Increased gel concentration in slurry injection, increased breaker concentration during fracture clean-up, and the flowback procedure are simulated to quantify the gel damage phenomenon. Features such as non-Darcy flow through fractures and polymer adsorption/desorption are included in the model. Parametric studies on the gel and breaker concentrations, reservoir properties, and flowback designs are also discussed. Our studies determined that interactions between breaker and gel can be fully integrated into numerical simulations. Tested with a variety of gel and breaker concentrations as well as the reaction dynamics, the numerical model is robust in quantifying the gel damage phenomenon in the fracture. Detailed numerical evaluations of gel damage effects with severe gel-damage zone inside the fracture are demonstrated in this paper. High gel residue concentration is observed at the tip of fractures due to high yield stress during flowback, which reduces the effective fracture drainage. Cleanup efficiency is highly dependent on the gel and breaker interactions. Based on parametric studies, optimized gel/breaker concentrations and sufficient interaction time can significantly reduce the gel residue inside the fracture and provide possibilities of having less gel damage in hydraulic fractures. The results provide new observations about improving well productivity through proper gel/breaker selection and flowback design.

Sustainable high fracture conductivity is a key to successful stimulation. The reduction of hydraulic fracture conductivity due to proppant deformation and crushing is frequently observed. Previous researches are based on laboratory experiments and empirical correlations, which can not fully explain proppant damage in field cases. In this paper, we applied our fully coupled fluid flow and geomechanical model to further understand the proppant pack deformation and crushing. Parametric studies on wellbore and reservoir pressures, formation properties, and proppant biot constant were performed to understand proppant deformation and crushing in different conditions. Additionally, an analytical model for avoiding proppant crushing was developed for fractured wells. Through this research, we found fracture conductivity loss due to deformation and crushing are severer than laboratory results. Large deformation and high probability of crushing were observed near wellbore according to the net pressure. Fast flow back (low bottom hole pressure) would generate large proppant crushed zone. Various reservoir properties as pressure gradient, formation stiffness, and matrix permeability were also investigated. Strong proppant is highly recommended for natural fractures, and hydraulic fracture near well bore especially for tight formations. Small chock size (high BHP) is also recommended during early production. Additionally, a simple analytical model is provided, accoding to the parametrical studies, for operating well without breaking proppant pack.

Fracture treatments have been proved to be the effective and efficient method in stimulating tight-gas reservoirs. The key is to create a long, highly conductive fracture to increase the well productivity and ultimate gas recovery. Since 1960s, fracture damage mechanisms have been investigated by petroleum engineers, researchers, and field personnel to better understand what caused lower fracture conductivity and shorter fracture lengths. Based on our critical and comprehensive literature review, we found that more than 20 damage factors have been understood and quantified. However, there is still no method available for identification of gel damage in the field. Based on numerical simulation results (Wang et al., 2008), we have developed a new type curve for identification of gel damage in tight gas wells. The type curve has been applied to six wells in the Cotton Valley formation of central Texas. The severity of gel damage in each well was ranked in the order of no damage, slight damage, medium damage, and severe damage. This type curve provides a new tool for practicing petroleum engineers to identify fracture damages in tight gas wells worldwide.

The ongoing low oil price environment has profound impact on all the operators and service providers. Efficiency improvements and cost reductions are two key strategies to capture the opportunities in current situation. It is now imperative for engineers to improve engineering practices to gain efficiency and drive down the cost. However, in well stimulation practices, it is vital to all stakeholders to obtain fracturing fluids with desirable fluid viscosity, and thermal and chemical properties with cost as low as reasonably possible. Preparing fracturing fluids with high-hardness produced water is one option to drive down cost. Such a practice eliminates the need to transport fresh water and dispose wastewater. However, it may not be possible because of the reaction tendencies between cations and functioning polymers within fracturing fluids. Although combinations of chemicals including polymers, chemical additives, stabilizers, and buffers can be added to prevent such reactions, the dosages of each component are often hard to quantify and often dependent on the experience of field engineers. A fast prognosis tool has been developed to facilitate such a decision-making process by identifying the lowest possible dosages of chemicals dependent on produced water hardness. With such a prognosis tool, it is now possible to make more educated and cost-effective plans to optimize the engineering practice. In this work, the underlying physics of hard water damage to fracturing fluids is discussed, followed by a demonstration of the simulations that reproduced the lab rheology experiment results. The viscosity profiles of a number of rheology experiments were first matched as model calibrations. The effects of different stabilizers were then discussed by parametric comparison of different cases. With the predictive model successfully capturing the reaction system, a dynamic algorithm was built to compute the lowest cost possible solution of functioning fracturing fluids in a given system. Due to the non-linear nature of the chemical reaction system, a searching algorithm was implemented to minimize the cost of fracturing fluids as functions of local produced water hardness, cost of each chemical component and operational expenses. This work demonstrates that good engineering practices are achieved through carefully understanding and modeling a working system, and through dynamic planning of the overall workflow with cost optimization as a target. All in the form of a prognosis tool that could be easily implemented in the current fracturing fluid preparation work flow.

Preparing fracturing fluids from low-quality water such as hard water is an environmentally friendly option in field operations and is therefore highly desirable. However, fluid viscosity can be significantly reduced when mixed in hard water rather than fresh water, requiring the addition of stabilizers to mitigate the hardness damages. Although some stabilizers have already been identified in experiments, systematic studies to help optimize fracturing fluids based on chemical compositions of produced water and the chemical properties of polymer and stabilizers are still needed. In this work, we use reactive transport model to understand how stabilizers mitigate water hardness damages in fracturing fluids prepared with hard water. We studied a system where several stabilizers have been proved to mitigate hard water damages to metal-crosslinked derivatized polysaccharide (MCDP) fracturing fluids. Reversible chemical reactions between MCDP and cations lead to polysaccharide salts precipitations that compromised the fluid viscosity. Stabilizers are chemically active substances that preferentially react with cations, especially divalent cations so they can protect MCDP from precipitating. To benchmark this system, reactive transport models were set up to explicitly consider the fluid viscosity alterations caused by the chemical reactions among polymers, cations and stabilizers in flow conditions relevant to regain conductivity tests (RCT). The numerical simulator was developed based on Crunchflow with the viscosity as a function of polymer and cation concentration. The viscosity profiles of a number of rheology experiments were first matched as model calibrations. The effects of different stabilizers were then determined by parametric comparison of different cases. The model was then verified by matching it to the rheology of fracturing fluids prepared in experiments by mixing MCDP and stabilizers with hard water samples. Simulation results show that the type of stabilizers and cations in the hard water has a significant impact on the viscosity alteration for the same level of MCDP added. Stabilizers mitigate the hardness damages either instantly or in a latent manner depending on their intrinsic reaction kinetics with cations. This work demonstrates that reactive transport model could be used to help design and optimize fracturing fluids according to laboratory tests and produced water compositions. It is believed to be the first time that reactive transport modeling is used to study the complicated interactions among polymers, cations and stabilizers in fracturing fluids.