The Experts below are selected from a list of 13791 Experts worldwide ranked by ideXlab platform
Timothy R Carr - One of the best experts on this subject based on the ideXlab platform.
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integrated data driven 3d shale Lithofacies modeling of the bakken formation in the williston basin north dakota united states
Journal of Petroleum Science and Engineering, 2019Co-Authors: Shuvajit Bhattacharya, Timothy R CarrAbstract:Abstract Integrated petrophysical analysis is used in conventional and unconventional reservoirs to visualize the distribution pattern of different Lithofacies and interpret depositional environments. In this study, core data from 17 wells and well logs from 517 wells are used to construct 3D data-driven Lithofacies models for the upper and lower shale members in the Bakken Formation of the Williston basin in North Dakota, United States. The principal objective of this multi-scale (core, well log, and regional) study is to use the petrophysical response of Lithofacies defined in core from a very limited number of wells to identify different shale Lithofacies in the Bakken Formation in the numerous and geographically extensive wells with wireline log suites. Shale Lithofacies are defined in the core using quantitative mineralogy, Total Organic Carbon content, and petrophysical properties. These Lithofacies are calibrated to advanced geochemical spectroscopy logs and conventional well logs at well scales. A machine learning algorithm, Support Vector Machine, is used to recognize the pattern of different shale Lithofacies, associated with basic petrophysical parameters from ubiquitous conventional well log suites. Sequential Indicator Simulation is used to populate all Lithofacies in a 3D grid, covering a large portion of the Williston basin in North Dakota. The results show that the Bakken shale members are vertically and laterally heterogeneous, but are successfully classified into five different Lithofacies. Organic-rich shale Lithofacies outweigh the proportion of organic-lean shale Lithofacies. It appears several factors influenced the pattern of shale Lithofacies distribution of the Bakken Formation.
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comparison of supervised and unsupervised approaches for mudstone Lithofacies classification case studies from the bakken and mahantango marcellus shale usa
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Shuvajit Bhattacharya, Timothy R Carr, Mahesh PalAbstract:Abstract Quantitative Lithofacies modeling is important to understand the depositional and diagenetic history, and hydrocarbon potential of unconventional resources at a regional scale. The complex heterogeneous nature and large data dimensionality of unconventional mudstone reservoirs increase the challenge of Lithofacies interpretation by conventional qualitative methods. Quantitative shale Lithofacies, which are meaningful, mappable, and predictable at core, well log, and regional scales, can be defined based on mineralogy and Total Organic Carbon (TOC) derived from core analysis and advanced geochemical spectroscopy logs (e.g. Pulsed Neutron Spectroscopy, PNS). However, access to numerous and widespread core samples and geochemical log responses is typically limited by cost and time. We apply different mathematical techniques to ubiquitous conventional well log suites calibrated to rock types, defined by the limited number of wells with high-quality core and geochemical logs. The documented interrelationships between Lithofacies and conventional logs are propagated with a quantified degree of accuracy in wells without advanced log or core data. Our study addresses issues of different approaches of quantitative Lithofacies classification and prediction techniques from well logs. Various data-driven supervised and unsupervised computational approaches, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Self-Organizing Map (SOM) and Multi-Resolution Graph-based Clustering (MRGC), are applied and compared to reduce uncertainty of propagating single-well based Lithofacies analysis, and efficiently understand geological trends. Two different dataset from the Devonian Bakken and Mahantango-Marcellus Shale formations in North America are used, in order to undertake a comparative assessment of computational techniques for Lithofacies characterization. Original shale Lithofacies, defined from geochemical logs and core data, are used to compare the results of selected supervised and unsupervised computational approaches. The results show that both Bakken and Mahantango-Marcellus shale members are vertically and laterally heterogeneous, but can be classified into at least five mudstone Lithofacies, along with calcareous siltstone and limestone Lithofacies. SVM works better than other techniques for Lithofacies classification and prediction in reduced computational time, no iteration, and with highly repeatable results. Accuracy of Lithofacies prediction increases if the algorithms are supervised with geological rules.
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identifying organic rich marcellus shale Lithofacies by support vector machine classifier in the appalachian basin
Computers & Geosciences, 2014Co-Authors: Guochang Wang, Timothy R CarrAbstract:Unconventional shale reservoirs as the result of extremely low matrix permeability, higher potential gas productivity requires not only sufficient gas-in-place, but also a high concentration of brittle minerals (silica and/or carbonate) that is amenable to hydraulic fracturing. Shale Lithofacies is primarily defined by mineral composition and organic matter richness, and its representation as a 3-D model has advantages in recognizing productive zones of shale-gas reservoirs, designing horizontal wells and stimulation strategy, and aiding in understanding depositional process of organic-rich shale. A challenging and key step is to effectively recognize shale Lithofacies from well conventional logs, where the relationship is very complex and nonlinear. In the recognition of shale Lithofacies, the application of support vector machine (SVM), which underlies statistical learning theory and structural risk minimization principle, is superior to the traditional empirical risk minimization principle employed by artificial neural network (ANN). We propose SVM classifier combined with learning algorithms, such as grid searching, genetic algorithm and particle swarm optimization, and various kernel functions the approach to identify Marcellus Shale Lithofacies. Compared with ANN classifiers, the experimental results of SVM classifiers showed higher cross-validation accuracy, better stability and less computational time cost. The SVM classifier with radius basis function as kernel worked best as it is trained by particle swarm optimization. The Lithofacies predicted using the SVM classifier are used to build a 3-D Marcellus Shale Lithofacies model, which assists in identifying higher productive zones, especially with thermal maturity and natural fractures.
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organic rich marcellus shale Lithofacies modeling and distribution pattern analysis in the appalachian basin
AAPG Bulletin, 2013Co-Authors: Guochang Wang, Timothy R CarrAbstract:The Marcellus Shale is considered to be the largest unconventional shale-gas resource in the United States. Two critical factors for unconventional shale reservoirs are the response of a unit to hydraulic fracture stimulation and gas content. The fracture attributes reflect the geomechanical properties of the rocks, which are partly related to rock mineralogy. The natural gas content of a shale reservoir rock is strongly linked to organic matter content, measured by total organic carbon (TOC). A mudstone Lithofacies is a vertically and laterally continuous zone with similar mineral composition, rock geomechanical properties, and TOC content. Core, log, and seismic data were used to build a three-dimensional (3-D) mudrock Lithofacies model from core to wells and, finally, to regional scale. An artificial neural network was used for Lithofacies prediction. Eight petrophysical parameters derived from conventional logs were determined as critical inputs. Advanced logs, such as pulsed neutron spectroscopy, with log-determined mineral composition and TOC data were used to improve and confirm the quantitative relationship between conventional logs and Lithofacies. Sequential indicator simulation performed well for 3-D modeling of Marcellus Shale Lithofacies. The interplay of dilution by terrigenous detritus, organic matter productivity, and organic matter preservation and decomposition affected the distribution of Marcellus Shale Lithofacies distribution, which may be attributed to water depth and the distance to shoreline. The trend of normalized average gas production rate from horizontal wells supported our approach to modeling Marcellus Shale Lithofacies. The proposed 3-D modeling approach may be helpful for optimizing the design of horizontal well trajectories and hydraulic fracture stimulation strategies.
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organic rich marcellus shale Lithofacies modeling and distribution pattern analysis in the appalachian basin
AAPG Bulletin, 2013Co-Authors: Guochang Wang, Timothy R CarrAbstract:The Marcellus Shale is considered to be the largest unconventional shale-gas resource in the United States. Two critical factors for unconventional shale reservoirs are the response of a unit to hydraulic fracture stimulation and gas content. The fracture attributes reflect the geomechanical properties of the rocks, which are partly related to rock mineralogy. The natural gas content of a shale reservoir rock is strongly linked to organic matter content, measured by total organic carbon (TOC). A mudstone Lithofacies is a vertically and laterally continuous zone with similar mineral composition, rock geomechanical properties, and TOC content. Core, log, and seismic data were used to build a three-dimensional (3-D) mudrock Lithofacies model from core to wells and, finally, to regional scale. An artificial neural network was used for Lithofacies prediction. Eight petrophysical parameters derived from conventional logs were determined as critical inputs. Advanced logs, such as pulsed neutron spectroscopy, with log-determined mineral composition and TOC data were used to improve and confirm the quantitative relationship between conventional logs and Lithofacies. Sequential indicator simulation performed well for 3-D modeling of Marcellus Shale Lithofacies. The interplay of dilution by terrigenous detritus, organic matter productivity, and organic matter preservation and decomposition affected the distribution of Marcellus Shale Lithofacies distribution, which may be attributed to water depth and the distance to shoreline. The trend of normalized average gas production rate from horizontal wells supported our approach to modeling Marcellus Shale Lithofacies. The proposed 3-D modeling approach may be helpful for optimizing the design of horizontal well trajectories and hydraulic fracture stimulation strategies.
Guochang Wang - One of the best experts on this subject based on the ideXlab platform.
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longmaxi wufeng shale Lithofacies identification and 3 d modeling in the northern fuling gas field sichuan basin
Journal of Natural Gas Science and Engineering, 2017Co-Authors: Guochang Wang, Cheng Huang, Shengxiang Long, Yongmin PengAbstract:Abstract Mineral composition and total organic carbon (TOC) content of shale is related with rock brittleness and gas content, respectively. Shale Lithofacies defined by them can effectively describe the heterogeneity of shale gas reservoirs. Therefore, a 3-D model of shale Lithofacies was constructed for the Longmaxi-Wufeng Shale in Fuling Gas Field, Sichuan Basin. Firstly, three criteria were proposed to define ten shale Lithofacies in Longmaxi-Wufeng Shale. The core- and elementary capture spectroscopy (ECS)-defined shale Lithofacies with the wireline logs at their location consisted of a training dataset with 1044 sets of data for predicting shale Lithofacies by conventional logs. And, artificial neural network and hierarchical decomposition algorithms were developed to achieve this prediction. Due to the instability of horizontal wellbore, a process of quality control was completed to remove all the low-quality data. To construct the 3-D model using data primarily from horizontal wells, it is critical to fix at least two special issues which are not common for the cases using data from only vertical wells. The relationship between horizontal wells and formation surfaces become much more complex, and data from wells was biased and failed to represent the distribution feature of the study area. Methods, including establishing pseudo vertical wells to provide more formation data and constructing 3-D probability trend model, were developed in this research to overcome these issues. The 3-D modeling of shale Lithofacies is very helpful for optimizing the design of horizontal well trajectories and hydraulic fracture stimulation strategies.
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identifying organic rich marcellus shale Lithofacies by support vector machine classifier in the appalachian basin
Computers & Geosciences, 2014Co-Authors: Guochang Wang, Timothy R CarrAbstract:Unconventional shale reservoirs as the result of extremely low matrix permeability, higher potential gas productivity requires not only sufficient gas-in-place, but also a high concentration of brittle minerals (silica and/or carbonate) that is amenable to hydraulic fracturing. Shale Lithofacies is primarily defined by mineral composition and organic matter richness, and its representation as a 3-D model has advantages in recognizing productive zones of shale-gas reservoirs, designing horizontal wells and stimulation strategy, and aiding in understanding depositional process of organic-rich shale. A challenging and key step is to effectively recognize shale Lithofacies from well conventional logs, where the relationship is very complex and nonlinear. In the recognition of shale Lithofacies, the application of support vector machine (SVM), which underlies statistical learning theory and structural risk minimization principle, is superior to the traditional empirical risk minimization principle employed by artificial neural network (ANN). We propose SVM classifier combined with learning algorithms, such as grid searching, genetic algorithm and particle swarm optimization, and various kernel functions the approach to identify Marcellus Shale Lithofacies. Compared with ANN classifiers, the experimental results of SVM classifiers showed higher cross-validation accuracy, better stability and less computational time cost. The SVM classifier with radius basis function as kernel worked best as it is trained by particle swarm optimization. The Lithofacies predicted using the SVM classifier are used to build a 3-D Marcellus Shale Lithofacies model, which assists in identifying higher productive zones, especially with thermal maturity and natural fractures.
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organic rich marcellus shale Lithofacies modeling and distribution pattern analysis in the appalachian basin
AAPG Bulletin, 2013Co-Authors: Guochang Wang, Timothy R CarrAbstract:The Marcellus Shale is considered to be the largest unconventional shale-gas resource in the United States. Two critical factors for unconventional shale reservoirs are the response of a unit to hydraulic fracture stimulation and gas content. The fracture attributes reflect the geomechanical properties of the rocks, which are partly related to rock mineralogy. The natural gas content of a shale reservoir rock is strongly linked to organic matter content, measured by total organic carbon (TOC). A mudstone Lithofacies is a vertically and laterally continuous zone with similar mineral composition, rock geomechanical properties, and TOC content. Core, log, and seismic data were used to build a three-dimensional (3-D) mudrock Lithofacies model from core to wells and, finally, to regional scale. An artificial neural network was used for Lithofacies prediction. Eight petrophysical parameters derived from conventional logs were determined as critical inputs. Advanced logs, such as pulsed neutron spectroscopy, with log-determined mineral composition and TOC data were used to improve and confirm the quantitative relationship between conventional logs and Lithofacies. Sequential indicator simulation performed well for 3-D modeling of Marcellus Shale Lithofacies. The interplay of dilution by terrigenous detritus, organic matter productivity, and organic matter preservation and decomposition affected the distribution of Marcellus Shale Lithofacies distribution, which may be attributed to water depth and the distance to shoreline. The trend of normalized average gas production rate from horizontal wells supported our approach to modeling Marcellus Shale Lithofacies. The proposed 3-D modeling approach may be helpful for optimizing the design of horizontal well trajectories and hydraulic fracture stimulation strategies.
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organic rich marcellus shale Lithofacies modeling and distribution pattern analysis in the appalachian basin
AAPG Bulletin, 2013Co-Authors: Guochang Wang, Timothy R CarrAbstract:The Marcellus Shale is considered to be the largest unconventional shale-gas resource in the United States. Two critical factors for unconventional shale reservoirs are the response of a unit to hydraulic fracture stimulation and gas content. The fracture attributes reflect the geomechanical properties of the rocks, which are partly related to rock mineralogy. The natural gas content of a shale reservoir rock is strongly linked to organic matter content, measured by total organic carbon (TOC). A mudstone Lithofacies is a vertically and laterally continuous zone with similar mineral composition, rock geomechanical properties, and TOC content. Core, log, and seismic data were used to build a three-dimensional (3-D) mudrock Lithofacies model from core to wells and, finally, to regional scale. An artificial neural network was used for Lithofacies prediction. Eight petrophysical parameters derived from conventional logs were determined as critical inputs. Advanced logs, such as pulsed neutron spectroscopy, with log-determined mineral composition and TOC data were used to improve and confirm the quantitative relationship between conventional logs and Lithofacies. Sequential indicator simulation performed well for 3-D modeling of Marcellus Shale Lithofacies. The interplay of dilution by terrigenous detritus, organic matter productivity, and organic matter preservation and decomposition affected the distribution of Marcellus Shale Lithofacies distribution, which may be attributed to water depth and the distance to shoreline. The trend of normalized average gas production rate from horizontal wells supported our approach to modeling Marcellus Shale Lithofacies. The proposed 3-D modeling approach may be helpful for optimizing the design of horizontal well trajectories and hydraulic fracture stimulation strategies.
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the application of improved neuroevolution of augmenting topologies neural network in marcellus shale Lithofacies prediction
Computers & Geosciences, 2013Co-Authors: Guochang Wang, Guojian Cheng, Timothy R CarrAbstract:The organic-rich Marcellus Shale was deposited in a foreland basin during Middle Devonian. In terms of mineral composition and organic matter richness, we define seven mudrock Lithofacies: three organic-rich Lithofacies and four organic-poor Lithofacies. The 3D Lithofacies model is very helpful to determine geologic and engineering sweet spots, and consequently useful for designing horizontal well trajectories and stimulation strategies. The NeuroEvolution of Augmenting Topologies (NEAT) is relatively new idea in the design of neural networks, and shed light on classification (i.e., Marcellus Shale Lithofacies prediction). We have successfully enhanced the capability and efficiency of NEAT in three aspects. First, we introduced two new attributes of node gene, the node location and recurrent connection (RCC), to increase the calculation efficiency. Second, we evolved the population size from an initial small value to big, instead of using the constant value, which saves time and computer memory, especially for complex learning tasks. Third, in multiclass pattern recognition problems, we combined feature selection of input variables and modular neural network to automatically select input variables and optimize network topology for each binary classifier. These improvements were tested and verified by true if an odd number of its arguments are true and false otherwise (XOR) experiments, and were powerful for classification.
Shu Jiang - One of the best experts on this subject based on the ideXlab platform.
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pore structure characterization of different Lithofacies in marine shale a case study of the upper ordovician wufeng lower silurian longmaxi formation in the sichuan basin sw china
Journal of Natural Gas Science and Engineering, 2018Co-Authors: Shu Jiang, Xiaofeng LiuAbstract:Abstract Pore structure has distinct features in different shale Lithofacies. This paper presents a case study of the Upper Ordovician Wufeng-Lower Silurian Longmaxi formation in southeast Sichuan Basin to fully describe the characteristics of shale pore structure in different Lithofacies. 16 types of shale Lithofacies were classified using ternary diagram of siliceous minerals (quartz + feldspar, QF), carbonate minerals (Ca) and clay minerals (Cl). Among all, argillaceous-rich siliceous shale Lithofacies (S-3), argillaceous/siliceous mixed shale Lithofacies (M-2) and siliceous-rich argillaceous shale Lithofacies (CM-1) are the predominant Lithofacies. According to scanning electron microscope (SEM) images, combined with focused ion beam-scanning electron microscope (FIB-SEM), mercury intrusion porosimetry (MIP), and gas adsorption (N2 and CO2), the pore structure characteristics and its influencing factors were systematically analyzed. The results show that: Illite + illite/smectite minerals primarily influence the development of the inorganic pores in mixed clay and silica Lithofacies (CM-1). Clay minerals are protected from compaction by the rigid minerals, which significantly favors the development of mesopores (2–50 nm) and macropores (>50 nm). The abundance of organic matter is an important determinant for the organic pores in the siliceous Lithofacies (S-3), and TOC has a positive contribution to the development of micropores (
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effect of shale Lithofacies on pore structure of the wufeng longmaxi shale in the southeast chongqing china
Energy & Fuels, 2018Co-Authors: Luchuan Zhang, Lei Chen, Shu Jiang, Dianshi Xiao, Yang Liu, Yuying Zhang, Cheng GongAbstract:Total organic carbon (TOC), optical microscopy (OPM), field emission scanning electron mi-croscopy (FE-SEM), X-ray diffraction (XRD) and nitrogen gas adsorption (N2GA) analyses were performed on shale samples from the Upper Ordovician Wufeng Formation and the Lower Silurian Longmaxi Formation (Wufeng-Longmaxi Formation) in order to explore the effect of shale Lithofacies on pore structure. The results show that the Wufeng-Longmaxi shale consists of four types of pores: organic matter pores, interparticle pores, intraparticle pores and micro-fracture pores. A total of 8 kinds of shale Lithofacies were identified on the basis of TOC and the ternary diagram of siliceous minerals (quartz and feldspar), clay and carbonate. The geological properties have substantial heterogeneity in these shale Lithofacies. The volumes of organic matter (OM), clay-related and brittle mineral-related pores are 0.00119-0.01262 cm3/g, 0.00080-0.00260 cm3/g, and 0.00122-0.00215 cm3/g, with an average proportion of 51.85 %, 26.44 % ...
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Lithofacies characteristics and its effect on gas storage of the silurian longmaxi marine shale in the southeast sichuan basin china
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Zhenxue Jiang, Lei Chen, Hexin Huang, Shu Jiang, Xianglu Tang, Liu Yang, Fengyang Xiong, Jie FengAbstract:Abstract Based on a detailed description and analysis of outcrops and drilling cores, onsite gas desorption, and laboratory testing data, shale Lithofacies characteristics and its effect on gas storage of the Silurian Longmaxi Formation marine shale in the southeast Sichuan Basin have been studied. Twelve types of shale Lithofacies are classified based on the organic matter content and mineral composition, of which 9 types were identified in the study area based on their dramatically differences in color, grain size, lamination, organic matter content, mineralogy, density, and other physical properties. The bottom of the Longmaxi shale Formation is primarily organic-rich siliceous shale with stable distribution of thickness and good continuity. The upper section has characteristics of rapid vertical and lateral change in Lithofacies, exhibiting a strong spatial heterogeneity. Organic-rich siliceous shale in the lower section, showing the highest content of gas desorption in situ, has a high content of organic matter, a high brittleness index and good permeability, which is conducive to shale gas storage, hydraulic fracturing, and exploitation. Organic-rich argillaceous shale was also observed to have the highest methane adsorption capacity. The interval with Lithofacies association of organic-rich siliceous shale with organic-rich argillaceous shale interlayer is the pay zone for shale gas generation and accumulation.
Zhenxue Jiang - One of the best experts on this subject based on the ideXlab platform.
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effect of sedimentary environment on shale Lithofacies in the lower third member of the shahejie formation zhanhua sag eastern china
Interpretation, 2017Co-Authors: Zhenxue Jiang, Yuan Yuan, Pengfei Wang, Guoheng Liu, Bo Zhang, Chuanxiang Ning, Zhi WangAbstract:AbstractResearch on shale Lithofacies is important for shale oil and gas production. This study focused on the lower third member of the Shahejie Formation (Es3l) in the Luo-69 well in the Zhanhua Sag, Jiyang Depression, Bohai Bay Basin, eastern China. Several methods, including thin section observations, total organic carbon (TOC) analysis, X-ray diffraction analysis, quantitative evaluations of minerals by scanning electron microscopy, major and trace-element analyses, and field emission-scanning electron microscopy, are used to investigate the effect of sedimentary environment on the type and distribution of shale Lithofacies. Our research indicates that 36 types of shale Lithofacies can be classified based on the TOC content, mineral composition, and sedimentary structure, of which five types are identified in the study area. The Es3l shale has a high calcareous mineral content (average of 49.64%), low clay and siliceous minerals contents (averages of 19.54% and 19.02%, respectively), a high TOC conte...
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Lithofacies classification and its effect on pore structure of the cambrian marine shale in the upper yangtze platform south china evidence from fe sem and gas adsorption analysis
Journal of Petroleum Science and Engineering, 2017Co-Authors: Pengfei Wang, Zhenxue Jiang, Lei Chen, Lishi Yin, Chen Zhang, Pu HuangAbstract:Abstract Lithofacies classification and storage capacity are of great significance for shale gas. In this study, shale Lithofacies classification and its effect on pore structure from the Niutitang shale in the Upper Yangtze Platform were analyzed by experiments of field emission scanning electron microscope (FE-SEM) and gas adsorption analysis. Results show that Niutitang shale can be divided into 12 kinds of shale Lithofacies on the basis of TOC content and mineral composition. Pore types and size distribution are significantly distinct of different shale Lithofacies since TOC content and mineral compositions do affect shale pore structure differently in their own ways. Specifically, TOC content has the most significant positive effect on shale pore structure, indicating that the higher the TOC content is, the larger the pore volume and surface area are. Negative correlation has been found between calcareous mineral and pore volume and surface area, indicating the decrease of pore volume and surface area with the increase of calcareous mineral content. Compared to argillaceous mineral, siliceous mineral has stronger effect on pore structure. Pore types are also distinctly different in different shale Lithofacies which also significantly affect shale gas storage capacity. Organic matter pore is the most abundant pore type in the organic-rich siliceous shale while no OM pore has been found in the organic-poor calcareous shale. Above all, the organic-rich siliceous shale has the largest pore surface area as well as gas storage capacity. While the organic-poor calcareous shale has the smallest gas storage capacity with the poor pore volume and surface area. It would be an effective method to optimize the favorable shale Lithofacies in guiding the exploration and development of shale gas.
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effect of Lithofacies on gas storage capacity of marine and continental shales in the sichuan basin china
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Lei Chen, Zhenxue Jiang, Pengfei Wang, Bo Zhang, Keyu Liu, Fenglin Gao, Hexin HuangAbstract:Abstract Lithofacies types of the marine shale of the Lower Cambrian Qiongzhusi Formation in the southwestern Sichuan Basin and the continental shale of the fifth member of Upper Triassic Xujiahe Formation in the western Sichuan Basin were classified based on a modified three-end diagram concerning the contents of siliceous minerals, carbonate minerals and clay minerals. Various experiments including X-ray diffraction, low pressure nitrogen adsorption, high pressure methane adsorption, and gas content measurement were designed for comparative analyses among different Lithofacies in terms of core, pore structure, methane adsorption and gas-bearing characteristics. Then, the discrepancies between marine and continental shales Lithofacies were analyzed, and the effects of Lithofacies on gas adsorption and storage capacities were investigated. It is demonstrated that there are mainly five types of Lithofacies developed in the marine shale of the study area, namely siliceous shale Lithofacies (S), mixed siliceous shale Lithofacies (S-2), clay-rich siliceous shale Lithofacies (S-3), silica-rich argillaceous shale Lithofacies (CM-1), and argillaceous/siliceous mixed shale Lithofacies (M-2), while there are also mainly five types of Lithofacies developed in the continental shale of the study area, which are carbonate-rich siliceous shale Lithofacies (S-1), mixed siliceous shale Lithofacies (S-2), clay-rich siliceous shale Lithofacies (S-3), silica-rich argillaceous shale Lithofacies (CM-1), and argillaceous/siliceous mixed shale Lithofacies (M-2). Geological characteristics significantly vary among different Lithofacies in terms of core, pore structure, methane adsorption and gas-bearing characteristics. Compared to the continental shale Lithofacies, the marine shale Lithofacies was characterized by a higher proportion of siliceous shale Lithofacies group and a lower proportion of argillaceous shale Lithofacies group, which could be attributed to different sedimentary environments and sediment provenances. On the condition that the organic matter content keeps constant, the silica-rich argillaceous shale Lithofacies (CM-1) is favorable for adsorbed gas storage due to its strong methane adsorption capacity resulting from the highest clay minerals content, while the siliceous shale Lithofacies group is favorable for gas storage due to its well-preserved primary and organic pores resulting from the highest siliceous mineral content.
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Lithofacies characteristics and its effect on gas storage of the silurian longmaxi marine shale in the southeast sichuan basin china
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Zhenxue Jiang, Lei Chen, Hexin Huang, Shu Jiang, Xianglu Tang, Liu Yang, Fengyang Xiong, Jie FengAbstract:Abstract Based on a detailed description and analysis of outcrops and drilling cores, onsite gas desorption, and laboratory testing data, shale Lithofacies characteristics and its effect on gas storage of the Silurian Longmaxi Formation marine shale in the southeast Sichuan Basin have been studied. Twelve types of shale Lithofacies are classified based on the organic matter content and mineral composition, of which 9 types were identified in the study area based on their dramatically differences in color, grain size, lamination, organic matter content, mineralogy, density, and other physical properties. The bottom of the Longmaxi shale Formation is primarily organic-rich siliceous shale with stable distribution of thickness and good continuity. The upper section has characteristics of rapid vertical and lateral change in Lithofacies, exhibiting a strong spatial heterogeneity. Organic-rich siliceous shale in the lower section, showing the highest content of gas desorption in situ, has a high content of organic matter, a high brittleness index and good permeability, which is conducive to shale gas storage, hydraulic fracturing, and exploitation. Organic-rich argillaceous shale was also observed to have the highest methane adsorption capacity. The interval with Lithofacies association of organic-rich siliceous shale with organic-rich argillaceous shale interlayer is the pay zone for shale gas generation and accumulation.
Lei Chen - One of the best experts on this subject based on the ideXlab platform.
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effect of shale Lithofacies on pore structure of the wufeng longmaxi shale in the southeast chongqing china
Energy & Fuels, 2018Co-Authors: Luchuan Zhang, Lei Chen, Shu Jiang, Dianshi Xiao, Yang Liu, Yuying Zhang, Cheng GongAbstract:Total organic carbon (TOC), optical microscopy (OPM), field emission scanning electron mi-croscopy (FE-SEM), X-ray diffraction (XRD) and nitrogen gas adsorption (N2GA) analyses were performed on shale samples from the Upper Ordovician Wufeng Formation and the Lower Silurian Longmaxi Formation (Wufeng-Longmaxi Formation) in order to explore the effect of shale Lithofacies on pore structure. The results show that the Wufeng-Longmaxi shale consists of four types of pores: organic matter pores, interparticle pores, intraparticle pores and micro-fracture pores. A total of 8 kinds of shale Lithofacies were identified on the basis of TOC and the ternary diagram of siliceous minerals (quartz and feldspar), clay and carbonate. The geological properties have substantial heterogeneity in these shale Lithofacies. The volumes of organic matter (OM), clay-related and brittle mineral-related pores are 0.00119-0.01262 cm3/g, 0.00080-0.00260 cm3/g, and 0.00122-0.00215 cm3/g, with an average proportion of 51.85 %, 26.44 % ...
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Lithofacies classification and its effect on pore structure of the cambrian marine shale in the upper yangtze platform south china evidence from fe sem and gas adsorption analysis
Journal of Petroleum Science and Engineering, 2017Co-Authors: Pengfei Wang, Zhenxue Jiang, Lei Chen, Lishi Yin, Chen Zhang, Pu HuangAbstract:Abstract Lithofacies classification and storage capacity are of great significance for shale gas. In this study, shale Lithofacies classification and its effect on pore structure from the Niutitang shale in the Upper Yangtze Platform were analyzed by experiments of field emission scanning electron microscope (FE-SEM) and gas adsorption analysis. Results show that Niutitang shale can be divided into 12 kinds of shale Lithofacies on the basis of TOC content and mineral composition. Pore types and size distribution are significantly distinct of different shale Lithofacies since TOC content and mineral compositions do affect shale pore structure differently in their own ways. Specifically, TOC content has the most significant positive effect on shale pore structure, indicating that the higher the TOC content is, the larger the pore volume and surface area are. Negative correlation has been found between calcareous mineral and pore volume and surface area, indicating the decrease of pore volume and surface area with the increase of calcareous mineral content. Compared to argillaceous mineral, siliceous mineral has stronger effect on pore structure. Pore types are also distinctly different in different shale Lithofacies which also significantly affect shale gas storage capacity. Organic matter pore is the most abundant pore type in the organic-rich siliceous shale while no OM pore has been found in the organic-poor calcareous shale. Above all, the organic-rich siliceous shale has the largest pore surface area as well as gas storage capacity. While the organic-poor calcareous shale has the smallest gas storage capacity with the poor pore volume and surface area. It would be an effective method to optimize the favorable shale Lithofacies in guiding the exploration and development of shale gas.
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effect of Lithofacies on gas storage capacity of marine and continental shales in the sichuan basin china
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Lei Chen, Zhenxue Jiang, Pengfei Wang, Bo Zhang, Keyu Liu, Fenglin Gao, Hexin HuangAbstract:Abstract Lithofacies types of the marine shale of the Lower Cambrian Qiongzhusi Formation in the southwestern Sichuan Basin and the continental shale of the fifth member of Upper Triassic Xujiahe Formation in the western Sichuan Basin were classified based on a modified three-end diagram concerning the contents of siliceous minerals, carbonate minerals and clay minerals. Various experiments including X-ray diffraction, low pressure nitrogen adsorption, high pressure methane adsorption, and gas content measurement were designed for comparative analyses among different Lithofacies in terms of core, pore structure, methane adsorption and gas-bearing characteristics. Then, the discrepancies between marine and continental shales Lithofacies were analyzed, and the effects of Lithofacies on gas adsorption and storage capacities were investigated. It is demonstrated that there are mainly five types of Lithofacies developed in the marine shale of the study area, namely siliceous shale Lithofacies (S), mixed siliceous shale Lithofacies (S-2), clay-rich siliceous shale Lithofacies (S-3), silica-rich argillaceous shale Lithofacies (CM-1), and argillaceous/siliceous mixed shale Lithofacies (M-2), while there are also mainly five types of Lithofacies developed in the continental shale of the study area, which are carbonate-rich siliceous shale Lithofacies (S-1), mixed siliceous shale Lithofacies (S-2), clay-rich siliceous shale Lithofacies (S-3), silica-rich argillaceous shale Lithofacies (CM-1), and argillaceous/siliceous mixed shale Lithofacies (M-2). Geological characteristics significantly vary among different Lithofacies in terms of core, pore structure, methane adsorption and gas-bearing characteristics. Compared to the continental shale Lithofacies, the marine shale Lithofacies was characterized by a higher proportion of siliceous shale Lithofacies group and a lower proportion of argillaceous shale Lithofacies group, which could be attributed to different sedimentary environments and sediment provenances. On the condition that the organic matter content keeps constant, the silica-rich argillaceous shale Lithofacies (CM-1) is favorable for adsorbed gas storage due to its strong methane adsorption capacity resulting from the highest clay minerals content, while the siliceous shale Lithofacies group is favorable for gas storage due to its well-preserved primary and organic pores resulting from the highest siliceous mineral content.
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Lithofacies characteristics and its effect on gas storage of the silurian longmaxi marine shale in the southeast sichuan basin china
Journal of Natural Gas Science and Engineering, 2016Co-Authors: Zhenxue Jiang, Lei Chen, Hexin Huang, Shu Jiang, Xianglu Tang, Liu Yang, Fengyang Xiong, Jie FengAbstract:Abstract Based on a detailed description and analysis of outcrops and drilling cores, onsite gas desorption, and laboratory testing data, shale Lithofacies characteristics and its effect on gas storage of the Silurian Longmaxi Formation marine shale in the southeast Sichuan Basin have been studied. Twelve types of shale Lithofacies are classified based on the organic matter content and mineral composition, of which 9 types were identified in the study area based on their dramatically differences in color, grain size, lamination, organic matter content, mineralogy, density, and other physical properties. The bottom of the Longmaxi shale Formation is primarily organic-rich siliceous shale with stable distribution of thickness and good continuity. The upper section has characteristics of rapid vertical and lateral change in Lithofacies, exhibiting a strong spatial heterogeneity. Organic-rich siliceous shale in the lower section, showing the highest content of gas desorption in situ, has a high content of organic matter, a high brittleness index and good permeability, which is conducive to shale gas storage, hydraulic fracturing, and exploitation. Organic-rich argillaceous shale was also observed to have the highest methane adsorption capacity. The interval with Lithofacies association of organic-rich siliceous shale with organic-rich argillaceous shale interlayer is the pay zone for shale gas generation and accumulation.