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The seismic attributes of water‐rich sandstone contain much information about the rock's physical properties and seismic wave parameters. They are commonly used to predict the rock's physical properties (e.g. porosity). However, the seismic attributes of water‐rich sandstone are affected by porosity, water saturation and thickness. To eliminate the influence of thickness on the porosity prediction of water‐rich sandstone and improve the accuracy of the porosity prediction, the authors propose a Lambert W–R transform method to isolate the contribution of thickness and porosity from seismic attributes. First, a rock physical model is used to calculate the equivalent elastic parameters of water‐rich sandstones with different porosity values and water saturation levels. Second, the seismic attribute dataset of water‐rich sandstone is established by forward modelling the seismic response of the wedge‐shaped water‐rich sandstone model, and the selection of sensitive physical properties is completed. Then, the transformation parameters (ζAhRs and ηAhRs) are obtained by Lambert W–R transformation, which is exponentially related to instantaneous amplitude. ζAhRs and ηAhRs are sensitive to thickness and porosity, respectively. Finally, an interpretative template for porosity prediction of water‐rich sandstone is established by cross‐plot analysis (ζAhRs and ηAhRs) and verified by a practical case. The verification results show that the porosity predicted by the interpretation template is consistent with drilling fluid consumption. However, it is lower than the porosity of logging constrained P‐wave impedance inversion. [ABSTRACT FROM AUTHOR]

The conventional Archie formula struggles with the interpretation of water saturation from resistivity well log data due to the increasing complexity of exploration targets. This challenge has prompted researchers to explore alternative physical parameters, such as acoustic characteristics, for breakthroughs. Clarifying the influencing factors of porous media acoustic characteristics is one of the most important approaches to help understanding the mechanism of acoustic characteristics of carbonate reservoirs. The article uses digital rock technology to characterize the pore structure, quantitatively identify fractures and pore structures in carbonate rocks, and establish digital models. Through conventional acoustic testing, the pressure wave (P-wave) and shear wave (S-wave) velocities of rock samples at different water saturations are obtained, and the dynamic elastic modulus is calculated. A finite element calculation model is established using the digital rock computational model to provide a basis for fluid saturation calculation methods. Based on real digital rock models, different combinations of virtual fractures are constructed, and factors affecting acoustic parameters are analyzed. The study finds that as porosity increases, the velocity difference between porous cores and fractured cores also increases. These findings provide important technical support and a theoretical basis for interpreting acoustic well logging data and evaluating carbonate reservoirs with different pore and fracture types. [ABSTRACT FROM AUTHOR]

Cross-formational water flow has the potential to significantly impact the economic feasibility and efficiency of coalbed methane (CBM) production, making it necessary to examine its effects on reservoir parameters such as cleat porosity and gas and water relative permeability curves, as well as total gas and water in place. To assess the extent of hydraulic connectivity and its consequences, well logs or zone isolation tests should be utilized to confirm hydraulic interaction in areas where cross-flow is suspected. This study discovered that high water saturation caused by hydraulic connections delays the peak of gas production. The results further indicate that there are significant differences between the relative permeability plots obtained from simulated production data and the initial relative permeability plots when cross-flow occurs. These findings have crucial implications for methane management in mining. The total water in place ranged from 40227 to 79428 STB, and the total gas in place ranged from 4.5 x 108 to 5.3 x 108 SFC/ton for the cases analyzed. Therefore, this paper's findings could aid in determining the hydraulic connection between coal beds and surrounding formations, as well as the influence of cross-formational flow on reservoir parameters obtained from Production Data Analysis (PDA). [ABSTRACT FROM AUTHOR]

Shale porosity measurements have crucial scientific and economical applications in unconventional petroleum systems. As a standard technique, liquid saturation methods, including water saturation (WS) and oil saturation (OS), have been widely used to measure the porosity of many rock types. For clay-rich shale reservoirs with high organic matter content, it is well known that the WS method may cause clay swelling and induce structural changes in the pore system. The OS method affects the accuracy of porosity measurements because of some of the oil being dissolved by kerogen within the shale; however, this has not received sufficient research attention. In this study, we compare the previously reported and newly tested OS porosities with helium (He) expansion porosity. Results show that OS porosity generally exceeds the He porosity. Furthermore, the higher the total organic carbon (TOC) content and lower the maturity of shale, the greater the difference between the OS and helium porosities. When using the OS method, the effect of kerogen-dissolved oil causes an overestimation of the shale porosity by ∼30%. To the best of our knowledge, this is the first time to note the kerogen-dissolve oil effects on OS porosity. Herein, we propose a new, simple, and effective correction method for estimating OS porosity that involves subtracting the kerogen-dissolved oil content from raw OS porosity. In addition, the quantification model of kerogen-dissolved oil capacity is established, taking into account the abundance and maturity of organic matter. Taking the He porosity as the benchmark, the absolute error of the corrected OS porosity does not exceed 1% and the average relative error is only ∼10%. The obtained results can help improve the accuracy of shale porosity evaluation methods. [ABSTRACT FROM AUTHOR]

In order to explore the relative permeability characteristics of gas-water in the crushed coal rock mass around the drilling hole of gas extraction, the gas-water coupling permeation test system of the crushed rock mass was used to carry out the gas-water coupling permeation test by using the steady-state osmosis method, and the variation characteristics of the coal sample permeability parameters with osmotic pressure and axial pressure were obtained, and the interaction relationship between the permeation parameters was analyzed. The results show that the porosity of the crushed coal mass under pressure shows a rapid decline, a slow decline and stabilization with the increase of axial pressure. With the increase of water saturation, the relative permeability of coal-like gases decreases rapidly, the relative permeability of water increases linearly, the relative permeability of gases and water shows a competitive relationship, and the sensitivity of gas permeability to water saturation is higher. The total permeability of gas and water decreases with the increase of the effective force, obeying the exponential function relationship, the effective force will affect the deformation process of the pore structure of the crushed coal rock mass, and with the decrease of porosity, the effective permeability of the gas decreases and the relative permeability increases. The influence of osmotic pressure on the relative permeability of water and gas can be divided into gas dominant stage, isotonic stage and water dominant stage, and the critical osmotic pressure extraction value ranges from 0.4 MPa to 0.6 MPa.

Four subsurface sections and electrical, porosity logs, and gamma-ray logs of the Khasib Formation (age Late Turonian-Lower Coniacian) were studied to identify reservoir characteristics and to evaluate the reservoir properties of the Khasib reservoir units in the East Baghdad oilfield. The lithology of the formation is limestone throughout the whole sequence in all studied wells EB-83, EB-87, EB-92, and EB94. It is bounded conformably from the top by Tanuma Formation and has a conformable lower contact with Kifl Formation. The lower and upper boundaries of the formation were determined using well log analysis, and the formation was divided into three main rock units (Kh1, Kh2, and Kh3), depending on the porosity logs. The porosity was calculated using acoustic or sonic, neutron, and density logs. The effective porosity (average 0.0 - 0.32 %) is the predominant porosity in the formation and to less extent; the secondary porosity. The volume of shale is very low (average 0.0 - 0.13 %), indicating limestone is the main rock of the Khasib Formation. The study of the reservoir water (average 0.11- 1.0%) and hydrocarbon saturations (average 0.0 - 0.88 %) showed that the formation contains varying proportions and quantities of water and hydrocarbons suspended in the wall void, and hydrocarbons capable of being produced. The lithological study reflected that the predominant lithic formation is limestone. It was found that Kh 2 unit is the best oil reservoir unit in all selected wells in terms of porosity, water saturation, diagenesis processes, and microfacies analysis. [ABSTRACT FROM AUTHOR]

Abstract The main objective of net pay determination, as an important step of any reservoir study, is to exclude non-reservoir intervals so that better results are obtained from reservoir characterization, hydrocarbon in-place calculations, and dynamic flow simulation of the reservoir. This study is a comprehensive presentation of the most applicable methods available for net pay determination, highlighting their strengths, limitations, and their input data, and presenting a new procedure to prepare the input data, determine the reservoir net pay, and validate the final results. These methods include conventional best-fit line and quadrant methods in a porosity–permeability cross-plot, Worthington method, rules of thumb, cumulative hydrocarbon column plot, and production constraints. This study, unlike previous ones, presents a stepwise methodology to reach the correct answer considering both rock and fluid properties. The necessity for the definition of net pay is discussed in the current study in the first step. Determination of net pay and the net-to-gross ratio is done by definition of some cut-off values for petrophysical properties such as porosity, water saturation, and shale volume. The new procedure presented in this study as a flowchart to determine pay zone uses different methods to determine cut-off values. The sequential and systematic use of all these methods gives a consistent and more reliable answer. The key steps to determine net pay is to find the porosity cut-off based on a porosity–permeability cross-plot and a pre-defined limiting value for permeability and then to use this value to find the shale volume and water saturation cut-offs using their cross-plots versus porosity. To take into account the fluid properties effect, a mobility cut-off is used as the starting point instead of permeability. Cumulative hydrocarbon column plots are used as a sensitivity tool to determine what percentage of the hydrocarbons will be discarded by any cut-off value. Finally, the determined net pay should be validated using the results of production logging and wireline formation tests. The proposed methodology was applied to a real field to determine its net pay. Porosity and water saturation cut-offs were calculated to be 2% and 55%, respectively, and due to the clean nature of the reservoir, a shale volume cut-off was not necessary. Simultaneous application of porosity and water saturation cut-offs discarded 6.3% of the hydrocarbon column for the field example.

The main objective of net pay determination, as an important step of any reservoir study, is to exclude non-reservoir intervals so that better results are obtained from reservoir characterization, hydrocarbon in-place calculations, and dynamic flow simulation of the reservoir. This study is a comprehensive presentation of the most applicable methods available for net pay determination, highlighting their strengths, limitations, and their input data, and presenting a new procedure to prepare the input data, determine the reservoir net pay, and validate the final results. These methods include conventional best-fit line and quadrant methods in a porosity–permeability cross-plot, Worthington method, rules of thumb, cumulative hydrocarbon column plot, and production constraints. This study, unlike previous ones, presents a stepwise methodology to reach the correct answer considering both rock and fluid properties. The necessity for the definition of net pay is discussed in the current study in the first step. Determination of net pay and the net-to-gross ratio is done by definition of some cut-off values for petrophysical properties such as porosity, water saturation, and shale volume. The new procedure presented in this study as a flowchart to determine pay zone uses different methods to determine cut-off values. The sequential and systematic use of all these methods gives a consistent and more reliable answer. The key steps to determine net pay is to find the porosity cut-off based on a porosity–permeability cross-plot and a pre-defined limiting value for permeability and then to use this value to find the shale volume and water saturation cut-offs using their cross-plots versus porosity. To take into account the fluid properties effect, a mobility cut-off is used as the starting point instead of permeability. Cumulative hydrocarbon column plots are used as a sensitivity tool to determine what percentage of the hydrocarbons will be discarded by any cut-off value. Finally, the determined net pay should be validated using the results of production logging and wireline formation tests. The proposed methodology was applied to a real field to determine its net pay. Porosity and water saturation cut-offs were calculated to be 2% and 55%, respectively, and due to the clean nature of the reservoir, a shale volume cut-off was not necessary. Simultaneous application of porosity and water saturation cut-offs discarded 6.3% of the hydrocarbon column for the field example. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pore space of tight sandstone samples exhibits fractal characteristics. Nuclear magnetic resonance is an effective method for pore size characterization. This paper focuses on fractal characteristics of pore size from nuclear magnetic resonance (NMR) of tight sandstone samples. The relationship between the fractal dimension from NMR with pore structure and water saturation is parameterized by analyzing experimental data. Based on it, a pore structure characterization and classification method for water-saturated tight sandstone and a water saturation prediction method in a gas-bearing sandstone reservoir have been proposed. To verify the models, the fractal dimension from NMR of 19 tight sandstone samples selected from the gas-bearing tight sandstone reservoir of Shahejie Formation in Nanpu Sag and that of 16 of them under different water saturation states are analyzed. The application result of new methods in the gas-bearing tight sandstone reservoir of Shahejie Formation in Nanpu Sag shows consistency with experimental data. This paper has facilitated the development of the NMR application by providing a non-electrical logging idea in reservoir quality evaluation and water saturation prediction. It provides a valuable scientific resource for reservoir engineering and petrophysics of unconventional reservoir types, such as tight sandstone, low porosity, and low permeability sandstone, shale, and carbonate rock reservoirs. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The characterization of carbonate rocks is not straightforward, as they often experience complex diagenetic processes causing them to expose wide variations in pore types. This research aims to characterize the properties of a carbonate reservoir with a complicated porous structure through rock physics principles and tools. Two representative wells from an oil field located in SW of Iran were selected, and two-dimensional (2D) and three-dimensional (3D) rock physics templates (RPTs) were constructed by employing the appropriate rock physics models. The porosity, water saturation, and pore type are considered reservoir parameters affecting carbonate rock's elastic properties and indicating the reservoir quality. The 2D RPTs described variations in two reservoir parameters in terms of elastic properties. However, they were not able to simultaneously characterize all three reservoir parameters. The proposed 3D RPTs revealed the underlying relationship of elastic properties with pore aspect ratio, water saturation, and porosity. To validate the constructed RPTs, well logging data, scanning electron microscope images, and thin section images were utilized. The RPTs were also employed to predict the reservoir properties quantitatively, and these predictions were compared with the petrophysical data. The average errors of the predicted porosity and water saturation by 3D RPT were, respectively, 1.22% and 6.66% for well A, and 2.65% and 8.18% for well B. The 2D RPTs provided three sets of predictions for porosity and water saturation (considering three specific pore aspect ratios of 0.03, 0.1, and 0.5), all with higher average errors compared to the predictions by 3D RPT for both wells. The obtained results proved that 3D RPT could predict reservoir properties more accurately. Finally, based on the estimated values of pore aspect ratio, water saturation, and porosity using 3D RPTs, the reservoir under study was divided into distinct depth intervals, and a quality level was assigned to each interval. The introduced rock physics-based procedure for a carbonate reservoir characterization could increase the reliability in predicting the reservoir properties, enhance the ability to detect the reservoir fluid, and thereby reduce the interpretation risk. [ABSTRACT FROM AUTHOR]

Marine deep shale gas represents the main target of future shale gas development in China. In order to identify the key parametric characteristics of deep shales, a comprehensive test method and application study was carried out based on LF-NMR technology. The results show that the NMR T2 spectrum of shales varied considerably in different states. A new NMR porosity and water saturation test method based on three-time measurements was established. The relative error between corrected NMR and water immersion porosity is reduced from 49.97% to 6.66%, while that between corrected NMR and weighing water saturation is reduced from 32.15% to 6.85%. By testing key parameters such as free water quantity, adsorbed water quantity, and average adsorption thickness, the NMR surface relaxivity of shale is determined and used to transform NMR T2 spectrum into pore size distribution. The NMR T2 spectra of individual sublayers also differ significantly. In order to quantitatively describe the distribution of spectral peaks, a new reservoir evaluation parameter, T2 geometric mean value (T2g), is proposed. Larger T2g values signify larger pores, broader average pore size distribution, and higher fluid mobility. With this parameter, qualitative description of pore size distribution can be transformed into quantitative characterization. When evaluating shale gas reservoirs, it is important to use multiple key parameters, among which NMR test results are an important indicator. LF-NMR testing is uniquely superior over other test methods as one or more NMR tests can provide abundant parametric information. The presented comprehensive NMR test method offers useful theoretical references for furthering the development and application of this technology in shale gas research.

Fine logging evaluation of reservoir parameters has important reference value for the sweet spot prediction of tight oil reservoirs. In this paper, taking the An 38 Block in the western Ordos Basin as an example, the process of fine logging evaluation of tight oil reservoir parameters is constructed. The research shows that the tight oil reservoirs in the Chang 7 Member in the study area belong to the delta front deposits, and two microfacies of underwater distributary channel and inter-distributary bay are developed. The main lithologies are detrital feldspar sandstone and feldspar sandstone, and the main pore types are intergranular pores and dissolution pores. The constant-rate mercury intrusion experiment shows that the target layer is dominated by micronscale pores with a size of 2-10 μm, and the throat radius is mainly distributed in 0.1-0.750μm. The target layer is characterized by tightness, high resistance and good oil-bearing properties. The physical properties, oil-bearing properties and electrical properties of tight oil reservoirs in the study area have a good corresponding relationship, and the electrical properties of the reservoirs can better reflect the properties of the reservoirs. The lithoelectric parameters of tight oil reservoirs were determined, and the logging interpretation methods of shale content, porosity, permeability and water saturation were constructed. This study can provide a reference for similar studies. [ABSTRACT FROM AUTHOR]

Predicting reservoir parameters accurately is of great significance in petroleum exploration and development. In this paper, we propose a reservoir parameter prediction method named a fusional temporal convolutional network (FTCN). Specifically, we first analyze the relationship between logging curves and reservoir parameters. Then, we build a temporal convolutional network and design a fusion module to improve the prediction results in curve inflection points, which integrates characteristics of the shallow convolution layer and the deep temporal convolution network. Finally, we conduct experiments on real logging datasets. The results indicate that compared with the baseline method, the mean square errors of FTCN are reduced by 0.23, 0.24 and 0.25 in predicting porosity, permeability, and water saturation, respectively, which shows that our method is more consistent with the actual reservoir geological conditions. Our innovation is that we propose a new reservoir parameter prediction method and introduce the fusion module in the model innovatively. Our main contribution is that this method can well predict reservoir parameters even when there are great changes in formation properties. Our research work can provide a reference for reservoir analysis, which is conducive to logging interpreters' efforts to analyze rock strata and identify oil and gas resources. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi National Journal of Earth Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract In an attempt to reduce the errors and uncertainties associated with predicting reservoir properties for static modeling, seismic inversion was integrated with artificial neural network for improved porosity and water saturation prediction in the undrilled prospective area of the study field, where hydrocarbon presence had been confirmed. Two supervised neural network techniques (MLFN and PNN) were adopted in the feasibility study performed to predict reservoir properties, using P-impedance volumes generated from model-based inversion process as the major secondary constraint parameter. Results of the feasibility study for predicted porosity with PNN gave a better result than MLFN, when correlated with well porosity, with a correlation coefficient of 0.96 and 0.69, respectively. Validation of the prediction revealed a cross-validation correlation of 0.88 and 0.26, respectively, for both techniques, when a random transfer function derived from a given well is applied on other well locations. Prediction of water saturation using PNN also gave a better result than MLFN with correlation coefficient of 0.97 and 0.57 and cross-validation correlation coefficient of 0.89 and 0.3, respectively. Hence, PNN technique was adopted to predict both reservoir properties in the field. The porosity and water saturation predicted from seismic in the prospective area were 24–30% and 20–30%, respectively. This indicates the presence of good quality hydrocarbon bearing sand within the prospective region of the studied reservoir. As such, the results from the integrated techniques can be relied upon to predict and populate static models with very good representative subsurface reservoir properties for reserves estimation before and after drilling wells in the prospective zone of reservoirs.

Water saturation estimation faced a great challenge in tight gas sandstone reservoirs because of the effect of pore structure and strong heterogeneity. The classic Archie’s equation cannot be always well used. To quantify the effect of pore structure to rock resistivity in tight gas sandstones, taking Triassic Xujiahe Formation of northwestern Sichuan Basin as an example, 35 core samples were recovered and applied for resistivity experiments in laboratory under the simulated formation temperature and pressure environment, and 18 of them were simultaneously applied for nuclear magnetic resonance (NMR) and high-pressure mercury injection experimental measurements. Relationships between pore structure and resistivity parameters were analyzed. The results clearly illustrated that cementation exponent (m) and saturation exponent (n) were heavily affected by pore structure. Rocks with superior pore structure contained relatively higher cementation exponent and lower saturation exponent, and vice versa. Afterward, we raised a parameter of pore size index, which was defined as the ratio of macropore and micro-pore percentage contents, to characterize rock pore structure, and established a model to calculate optimal saturation exponent from NMR data. Meanwhile, cementation exponent prediction model was also raised by combining with porosity and irreducible water saturation (Swirr). Combining with calculated cementation exponent and saturation exponent, we optimized the Archie’s equation to predict water saturation in our target tight gas sands. Field examples illustrated that the predicted cementation exponent and saturation exponent matched well with core-derived results. The absolute errors between predicted cementation exponent and saturation exponent with core-derived results were lower than 0.05 and 0.07, separately. By using optimized Archie’s equation, water saturations were precisely predicted from well logging data in our target tight gas sandstone reservoirs; whereas, the classic Archie’s equation underestimated formation water saturation. [ABSTRACT FROM AUTHOR]

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Copyright of Iraqi National Journal of Earth Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The research area was located in South Sumatra Basin on Air Benakat Formation at South-East Jambi Province. The research conducted to know productive the interest zone by petrophysics analysis (volume shale water saturation, and porosity) and its characteristics by well-log. The lithology of TRD Well is sandstone with a few foraminifera. The interpretation based on the petrophysical analysis porosity of the 7th zone on TRD-10 is average 12,4%, saturation water 19,4% and volume shale 6,2%; the 7th zone on TRD-11 well is average porosity 16,2%, saturation water 41,3%, and volume shale 22%; the 11th zone on TRD-14 well is average porosity 33,2%, saturation water 21,2% and volume shale 1,2%; The 6th zone TRD-15 well, porosity 7,02%, saturation water 32,3% and volume shale 5,6%; On the TRD-17 well of the 7th zone is average the porosity 9,04%, saturation water 25,6% and volume shale 4,6%; and 4th zone of TRD-19 well, porosity 23,2% Saturation water 13,5% and volume shale 7,1%. The characteristics of hydrocarbon reservoir on TRD Wells have low water saturation is less than 50%, porosity more than 5% and volume shale less than 25%. From the result of petrophysics parameter value used as the indicator of the productive zone and interpreted that sand reservoir on well TRD has potentially for the reservoir zone with gas prospect.

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and fluid saturation in carbonate rocks. A strong linear correlation between P-wave velocity and S-wave velocity and between P-wave velocity and density rock was found. The resulting linear equations can be used to estimate P-wave velocity from the S-wave velocity in the case of both. The results of multiple regression analysis indicated that the density, porosity, water-saturated, and shear wave velocity (VS) are strongly related to Vp.

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Predicting reservoir parameters accurately is of great significance in petroleum exploration and development. In this paper, we propose a reservoir parameter prediction method named a fusional temporal convolutional network (FTCN). Specifically, we first analyze the relationship between logging curves and reservoir parameters. Then, we build a temporal convolutional network and design a fusion module to improve the prediction results in curve inflection points, which integrates characteristics of the shallow convolution layer and the deep temporal convolution network. Finally, we conduct experiments on real logging datasets. The results indicate that compared with the baseline method, the mean square errors of FTCN are reduced by 0.23, 0.24 and 0.25 in predicting porosity, permeability, and water saturation, respectively, which shows that our method is more consistent with the actual reservoir geological conditions. Our innovation is that we propose a new reservoir parameter prediction method and introduce the fusion module in the model innovatively. Our main contribution is that this method can well predict reservoir parameters even when there are great changes in formation properties. Our research work can provide a reference for reservoir analysis, which is conducive to logging interpreters’ efforts to analyze rock strata and identify oil and gas resources.

In an attempt to reduce the errors and uncertainties associated with predicting reservoir properties for static modeling, seismic inversion was integrated with artificial neural network for improved porosity and water saturation prediction in the undrilled prospective area of the study field, where hydrocarbon presence had been confirmed. Two supervised neural network techniques (MLFN and PNN) were adopted in the feasibility study performed to predict reservoir properties, using P-impedance volumes generated from model-based inversion process as the major secondary constraint parameter. Results of the feasibility study for predicted porosity with PNN gave a better result than MLFN, when correlated with well porosity, with a correlation coefficient of 0.96 and 0.69, respectively. Validation of the prediction revealed a cross-validation correlation of 0.88 and 0.26, respectively, for both techniques, when a random transfer function derived from a given well is applied on other well locations. Prediction of water saturation using PNN also gave a better result than MLFN with correlation coefficient of 0.97 and 0.57 and cross-validation correlation coefficient of 0.89 and 0.3, respectively. Hence, PNN technique was adopted to predict both reservoir properties in the field. The porosity and water saturation predicted from seismic in the prospective area were 24–30% and 20–30%, respectively. This indicates the presence of good quality hydrocarbon bearing sand within the prospective region of the studied reservoir. As such, the results from the integrated techniques can be relied upon to predict and populate static models with very good representative subsurface reservoir properties for reserves estimation before and after drilling wells in the prospective zone of reservoirs. [ABSTRACT FROM AUTHOR]

The estimation of rock petrophysical parameters is an essential matter to characterize any reservoir. This research deals with the evaluation of effective porosity (Pe), shale volume (Vsh) and water saturation (Sw) of reservoirs at Kumait and Dujalia fields, which were analyzed from well log and seismic data. The absolute acoustic impedance (AI) and relative acoustic impedance (RAI) were derived from a model which is based on the inversion of seismic 3-D post-stack data. NahrUmr formation’s sand reservoirs are identified by the RAI section of the study area. Nahr Umr sand-2 unit in Kumait field is the main reservoir; its delineation depends on the available well logs and AI sections information. The results of well logging interpretation showed a decrease of Sw and Vsh and an increase of effective porosity in the oil reservoir area, which coincides with the decrease of AI values. The existence of the water reservoir in Du-2 well revealed a convergence of the results of AI and effective porosity with those of Kumait wells, along with and some differential results of Sw and Vsh values that may be related to changes in lithology and fluid density. [ABSTRACT FROM AUTHOR]

Berau Basin is assessed to have same potential in clastic sediments with Mesozoic and Paleozoic ages, where reservoirs and source rocks are similar to productive areas of hydrocarbons in Northwest Shield Australia. This study aims to identify the hydrocarbon prospect zones and potential rocks zones using petrophysical parameters, such as shale volume, porosity, water saturation and permeability. Petrophysical analysis of reservoir and source rock are carried out on three wells located in the Berau Basin, namely DI-1, DI-2 and DI-3 in Kembelangan and Tipuma Formation. Qualitative analysis shows that there are 4 reservoir rock zones and 4 source rock zones from thorough analysis of these three wells. Based on quantitative analysis of DI-1 well, it has an average shale volume (Vsh) 9.253%, effective porosity (PHIE) 20.68%, water saturation (Sw) 93.3% and permeability (k) 55.69 mD. DI-2 well’s average shale volume, effective porosity, water saturation and permeability values are 29.16%, 2.97%, 67.9% and 0.05 mD, respectively. In DI-3 well, average shale volume, effective porosity, water saturation and permeability values are 6.205%, 19.36%, 80.2% and 242.05 mD, respectively. From the reservoir zone of these three wells in Kembelangan Formation, there are no show any hydrocarbon prospect.

Copyright of Geominas is the property of FUNDA-GEOMINAS. (Fundacion de Egresados d Amigos de la Escuela de Ingenieria Geologica y de Minas) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An onshore gas field (hereafter called the R field—real name not revealed) is in the southeast coast of Tanzania which includes a Tertiary aged shaly sand formation (sand–shale sequences). The formation was penetrated by an exploration well R–X wherein no core was acquired, and there is no layer-wise published data of the petrophysical properties of the R field in the existing literature, which are essential to reserves estimation and production forecast. In this paper, the layer-wise interpretation of petrophysical properties was undertaken by using wireline logs to obtain parameters to build a reservoir simulation model. The properties extracted include shale volume, total and effective porosities, sand fractions and sand porosity, and water saturation. Shale volume was computed using Clavier equation from gamma ray. Density method was used to calculate total and effective porosities. Thomas–Stieber method was used to determine sand porosity and sand fraction, and water saturation was computed using Poupon–Leveaux model. The statistics of the parameters extracted are presented, where shale volume obtained that varies with zones is between 6 and 54% volume fraction, with both shale laminations and dispersed shale were identified. Total porosity obtained is in a range from 12 to 22%. Sand porosity varies between 15 and 25%, and sand fraction varies between 33 and 93% height fraction. Average water saturation obtained is between 32 and 49% volume fraction. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Carbonate rocks, along with sandstone, constitute the main reservoirs of oil and gas in the world. Examination of petrophysical properties includes parameters such as porosity, permeability and fluid saturation, lithological variations according to depth and hydrocarbon properties including effective and ineffective thickness and effective hydrocarbons column. Asmari reservoir of Bibi- Hakimeh oilfield is one of the tertiary carbonate reservoirs in Iran located 210 km southeast of Ahwaz. The reservoir is divided into 8 zones, each zone having its own petrological characteristics and lithology. Considering the fact that all three major lithologies of reservoirs (limestone, dolomite and Shale) exist in the Asmari reservoir of Bibi- Hakimeh oilfield, lithological study and its impact on petrophysical parameters of reservoirs are very important. Based on the assessments, zone 1 with more than 85% limestone has the most effective hydrocarbon column, the highest net thickness and the highest net to total thickness ratio, and due to its low water saturation (about 20% for effective zones), it has the best reservoir quality among the other zones. Following zone 1, zones 2 and 3 take the second and the third places, respectively. Zones 4 to 8 are below the water-oil interface, hence they are not included in productive zones and have lower reservoir quality. Zone 1 is considered as the best oil producing layer with respect to petrophysical parameters. [ABSTRACT FROM AUTHOR]

Porosity, shale volume, and fluid saturation are the most important parameters used to determine the characteristics of oil reservoirs. The kupal oil field has located in Dezful embayment. Illam formation introduced as a fractured reservoir at the southwest of Iran. In this study, wells No.48 and 54 investigated. Based on this study and using well logging diagrams, the main lithology determined Limestone. It is worth mentioning that substrates of shale, dolomite and in some cases anhydrite can see. As well as based on the performed study, this formation divided into three zones, including two permeable zones and one non-permeable zone. In the non-permeable section, main minerals have determined as clay, being types of Montmorillonite, Mix layers, and Illite. Base on Gr log, the average volume of shale in wells No. 48 and 54 was 8% to 17% respectively, that overall shows Low percent volume of shale. In this field, the amount of porosity increased from SE to NW. Accordingly, the well log plot, there are appropriate porosity and water saturation in this horizon. To enhance the accuracy of formation of water saturation calculations, we calculate it by software using Indonesian and Simandoux methods. Such that the average effective porosity and water saturation are 7.9 and 43.4 %, respectively. Finally, it can be stated this formation has poor to mean reservoir characteristic, but it can achieve reservoir capacity from some wells and adjacent fields. [ABSTRACT FROM AUTHOR]

Abstract To investigate the effect of the application of complex resistivity logging in sand-shale reservoirs, measurements of complex resistivity are performed on core plugs obtained from artificial clear sand samples and shaly sand samples with different clay types and contents in a frequency range of 40 Hz to 15 MHz. This paper discusses the relationship between the complex resistivity values of samples and their porosity, water saturation, salinity, ion type, clay content, and temperature using the Cole-Cole model to fit complex resistivity curves and obtain the model parameters R0 and τ, which represent the resistivity at zero frequency and the time constant respectively. The results show that τ has the same trend as R0 i.e., it decrease as porosity, water saturation, salinity, clay content and temperature increase. Based on the Archie model and Waxman-Smith model, the saturation evaluation model of τ is built. This study also extracts the slope of the real part of complex resistivity and explores the correlation between the slope and permeability. A model of slope can be used to predict permeability, and the model parameters are different for clear sand samples and different shaly sand samples. This study provides strong support for studies of the rock complex resistivity mechanism and the application of complex resistivity logging in oil and gas evaluation. Highlights • Complex resistivity measurements of artificial clear and shaly sands are conducted in a frequency range from 40Hz to 15MHz. • The effect of frequency, porosity, water saturation, salinity, ion type, clay content, and temperature are discussed. • A model for predicting saturation with the time constant of the Cole-Cole model is built. • A model for predicting permeability with the slope of the real part of complex resistivity is verified and developed. [ABSTRACT FROM AUTHOR]

Abstract Estimation of petrophysical parameters is an important issue of any reservoirs. Porosity, volume of shale and water saturation has been evaluated for reservoirs of Upper Assam basin, located in northeastern India from well log and seismic data. Absolute acoustic impedance (AAI) and relative acoustic impedance (RAI) are generated from model based inversion of 2-D post-stack seismic data. The top of geological formation, sand reservoirs, shale layers and discontinuities at faults are detected in RAI section under the study area. Tipam Sandstone (TS) and Barail Arenaceous Sandstone (BAS) are the main reservoirs, delineated from the logs of available wells and RAI section. Porosity section is obtained using porosity wavelet and porosity reflectivity from post-stack seismic data. Two multilayered feed forward neural network (MLFN) models are created with inputs: AAI, porosity, density and shear impedance and outputs: volume of shale and water saturation with single hidden layer. The estimated average porosity in TS and BAS reservoir varies from 30% to 36% and 18% to 30% respectively. The volume of shale and water saturation ranges from 10% to 30% and 20% to 60% in TS reservoir and 28% to 30% and 23% to 55% in BAS reservoir respectively. Graphical abstract Image 1 Highlights • Relative acoustic impedance inversion delineate reservoir tops. • Porosity section is generated using porosity wavelet technique. • Neural Network model development for Volume of Shale mapping. • Neural Network Model development for Water saturation prediction. • Estimation of Petrophysical parameters in reservoirs, Upper Assam Basin. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering (17264073) is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Determining petrophysical parameters and reservoir evaluation has special importance in the oil industry. The precise knowledge of these parameters allows the petroleum engineers to have the tools they need in a given field to study precisely the production stages and, with their knowledge, will be more capable of developing oilfields. In this study, two wells in Asmari reservoir in Mansour Abad oil field has been investigated, and reservoir properties such as porosity, shale volume, and water saturation have been calculated, and the volume of water and oi l have been determined. All calculations, cross-plots, and logs diagrams are done via software Geolog version 6.7.1. Studies show that the Asmari Formation in this field has a low average shale volume. On the other hand, Asmari reservoir has good porosity, especially in the upper part (Zone 3), and porosity variations of the field are not high. Also, the use of the M-N plot indicates the prevalence of carbonate lithology. In addition, based on Thorium-Potassium cross-plots, the dominant clay minerals were identified as Illite and mixed layer. [ABSTRACT FROM AUTHOR]