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Mukul M Sharma - One of the best experts on this subject based on the ideXlab platform.
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DetermIne In-Situ Stress and Characterize Complex Fractures In Naturally Fractured Reservoirs from Diagnostic Fracture Injection Tests
Rock Mechanics and Rock Engineering, 2019Co-Authors: Hanyi Wang, Mukul M SharmaAbstract:Estimation of In-Situ Stresses has significant applications In earth sciences and subsurface engIneerIng, such as fault zone studies, underground CO2 sequestration, nuclear waste repositories, oil and gas reservoir development, and geothermal energy exploitation. Over the past few decades, Diagnostic Fracture Injection Tests (DFIT), which have also been referred to as Injection-Falloff Tests, Fracture Calibration Tests, and MIni-Frac Tests, have evolved Into a commonly used and reliable technique to obtaIn In-Situ Stress. SimplifyIng assumptions used In traditional methods often lead to Inaccurate estimation of the In-Situ Stress, even for a planar fracture geometry. When a DFIT is conducted In naturally fractured reservoirs, the stimulated natural fractures can either alter the effective reservoir permeability withIn the distance of Investigation or Interact with the hydraulic fracture to form a complex fracture geometry, this further complicates Stress estimation. In this study, we present a new pressure transient model for DFIT analysis In naturally fractured reservoirs. By analyzIng synthetic, laboratory and field cases, we found that fracture complexity and permeability evolution can be detected from DFIT data. Most importantly, it is shown that usIng established methods to pick mInimum In-Situ Stress often lead to over or underestimates, regardless of whether the reservoir is heavily fractured or sparsely fractured. Our proposed “variable compliance method” gives a much more accurate and reliable estimation of In-Situ Stress In both homogenous and naturally fractured reservoirs. By combInIng the unique pressure signatures associated with the closure of natural fractures, a lower bound on the horizontal Stress anisotropy can be estimated.
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new variable compliance method for estimatIng In Situ Stress and leak off from dfit data
arXiv: Geophysics, 2017Co-Authors: Hanyi Wang, Mukul M SharmaAbstract:It is shown that usIng Carter leak-off is an oversimplification that leads to significant errors In the Interpretation of DFIT data. Most importantly, this article reveals that previous methods of estimatIng mInimum In-Situ Stress often lead to significant over or underestimates. Based on our modelIng and simulation results, we propose a much more accurate and reliable method to estimate the mInimum In-Situ Stress and fracture pressure dependent leak-off rate.
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new variable compliance method for estimatIng In Situ Stress and leak off from dfit data
SPE Annual Technical Conference and Exhibition, 2017Co-Authors: Hanyi Wang, Mukul M SharmaAbstract:Over the past two decades, Diagnostic Fracture Injection Tests (DFIT), which have also been referred to as Injection-Falloff Tests, Fracture Calibration Tests, MIni-Frac Tests In the literature, have evolved Into a commonly used and reliable technique to evaluate reservoir properties, fracturIng parameters and obtaIn In-Situ Stresses. SInce the Introduction of DFIT analysis based on G-function and its derivative, this method has become standard practice for quantifyIng mInimum In-Situ Stress and leak-off coefficient. However, the pressure declIne model that underlies the G-function plot makes two distInct and important assumptions: (1) leak-off is not pressure-dependent and, (2) fracture stiffness (or compliance) is assumed to be constant durIng fracture closure. In this study, we first review Nolte's origInal G-function model and examIne the assumptions Inherent In the model. We then present a new global pressure transient model for pressure declIne after shut-In which not only preserves the physics of unsteady-state reservoir flow behavior, elastic fracture mechanics and material balance, but also Incorporates the gradual changes of fracture stiffness (or compliance) due to the contact of rough fracture walls durIng closure. Analysis of synthetic cases, along with field data are presented to demonstrate how the coupled effects of fracture geometry, fracture surface asperities, formation properties, pore pressure and wellbore storage can impact fracturIng pressure declIne and the estimation of mInimum In-Situ Stress. It is shown that usIng Carter's leak-off is an oversimplification that leads to significant errors In the Interpretation of DFIT data. Most importantly, this article reveals that previous methods of estimatIng mInimum In-Situ Stress often lead to significant over or underestimates. Based on our modelIng and simulation results, we propose a much more accurate and reliable method to estimate the mInimum In-Situ Stress and fracture pressure dependent leak-off rate.
Samuel Ameri - One of the best experts on this subject based on the ideXlab platform.
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DetermInIng In-Situ Stress Profiles From Logs
SPE Annual Technical Conference and Exhibition, 2004Co-Authors: Shahab D. Mohaghegh, Andrei Popa, Razi Gaskari, S. Wolhart, R. Siegfreid, Samuel AmeriAbstract:This paper presents a new and novel technique for determInIng the In-Situ Stress profile of hydrocarbon reservoirs from geophysical well logs usIng a combInation of fuzzy logic and neural networks. It is well established, that In-Situ Stress cannot be generated from well logs alone. This is because two sets of formations may have very similar geologic signatures but possess different In-Situ Stress profiles because of varyIng degrees of tectonic activities In each region. By usIng two new parameters as surrogates for tectonic activities, fuzzy logic to Interpret the logs and rank parameter Influence, and neural networks as a mappIng tool, it has become possible to accurately generate In-Situ Stress profiles from logs. This paper demonstrates the improved performance of this new approach over conventional approaches used In the Industry.
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DetermInIng In-Situ Stress profiles of hydrocarbon reservoirs from geophysical well logs usIng Intelligent systems
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541), 2004Co-Authors: Shahab D. Mohaghegh, Andrei Popa, Razi Gaskari, S. Wolhart, B. Siegfried, Samuel AmeriAbstract:This work presents a new and novel technique for determInIng the In-Situ Stress profile of hydrocarbon reservoirs from geophysical well logs usIng a combInation of fuzzy logic and neural networks. It is well established, that In-Situ Stress cannot be generated from well logs alone. This is because two sets of formations may have very similar geologic signatures but possess different In-Situ Stress profiles because of varyIng degrees of tectonic activities In each region. By usIng two new parameters as surrogates for tectonic activities, fuzzy logic to Interpret the logs and rank parameter Influence, and neural network as a mappIng tool, it has become possible to accurately generate In-Situ Stress profiles. This paper demonstrates the superiority of this new approach over conventional approaches used In the oil and gas Industry.
Hanyi Wang - One of the best experts on this subject based on the ideXlab platform.
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DetermIne In-Situ Stress and Characterize Complex Fractures In Naturally Fractured Reservoirs from Diagnostic Fracture Injection Tests
Rock Mechanics and Rock Engineering, 2019Co-Authors: Hanyi Wang, Mukul M SharmaAbstract:Estimation of In-Situ Stresses has significant applications In earth sciences and subsurface engIneerIng, such as fault zone studies, underground CO2 sequestration, nuclear waste repositories, oil and gas reservoir development, and geothermal energy exploitation. Over the past few decades, Diagnostic Fracture Injection Tests (DFIT), which have also been referred to as Injection-Falloff Tests, Fracture Calibration Tests, and MIni-Frac Tests, have evolved Into a commonly used and reliable technique to obtaIn In-Situ Stress. SimplifyIng assumptions used In traditional methods often lead to Inaccurate estimation of the In-Situ Stress, even for a planar fracture geometry. When a DFIT is conducted In naturally fractured reservoirs, the stimulated natural fractures can either alter the effective reservoir permeability withIn the distance of Investigation or Interact with the hydraulic fracture to form a complex fracture geometry, this further complicates Stress estimation. In this study, we present a new pressure transient model for DFIT analysis In naturally fractured reservoirs. By analyzIng synthetic, laboratory and field cases, we found that fracture complexity and permeability evolution can be detected from DFIT data. Most importantly, it is shown that usIng established methods to pick mInimum In-Situ Stress often lead to over or underestimates, regardless of whether the reservoir is heavily fractured or sparsely fractured. Our proposed “variable compliance method” gives a much more accurate and reliable estimation of In-Situ Stress In both homogenous and naturally fractured reservoirs. By combInIng the unique pressure signatures associated with the closure of natural fractures, a lower bound on the horizontal Stress anisotropy can be estimated.
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new variable compliance method for estimatIng In Situ Stress and leak off from dfit data
arXiv: Geophysics, 2017Co-Authors: Hanyi Wang, Mukul M SharmaAbstract:It is shown that usIng Carter leak-off is an oversimplification that leads to significant errors In the Interpretation of DFIT data. Most importantly, this article reveals that previous methods of estimatIng mInimum In-Situ Stress often lead to significant over or underestimates. Based on our modelIng and simulation results, we propose a much more accurate and reliable method to estimate the mInimum In-Situ Stress and fracture pressure dependent leak-off rate.
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new variable compliance method for estimatIng In Situ Stress and leak off from dfit data
SPE Annual Technical Conference and Exhibition, 2017Co-Authors: Hanyi Wang, Mukul M SharmaAbstract:Over the past two decades, Diagnostic Fracture Injection Tests (DFIT), which have also been referred to as Injection-Falloff Tests, Fracture Calibration Tests, MIni-Frac Tests In the literature, have evolved Into a commonly used and reliable technique to evaluate reservoir properties, fracturIng parameters and obtaIn In-Situ Stresses. SInce the Introduction of DFIT analysis based on G-function and its derivative, this method has become standard practice for quantifyIng mInimum In-Situ Stress and leak-off coefficient. However, the pressure declIne model that underlies the G-function plot makes two distInct and important assumptions: (1) leak-off is not pressure-dependent and, (2) fracture stiffness (or compliance) is assumed to be constant durIng fracture closure. In this study, we first review Nolte's origInal G-function model and examIne the assumptions Inherent In the model. We then present a new global pressure transient model for pressure declIne after shut-In which not only preserves the physics of unsteady-state reservoir flow behavior, elastic fracture mechanics and material balance, but also Incorporates the gradual changes of fracture stiffness (or compliance) due to the contact of rough fracture walls durIng closure. Analysis of synthetic cases, along with field data are presented to demonstrate how the coupled effects of fracture geometry, fracture surface asperities, formation properties, pore pressure and wellbore storage can impact fracturIng pressure declIne and the estimation of mInimum In-Situ Stress. It is shown that usIng Carter's leak-off is an oversimplification that leads to significant errors In the Interpretation of DFIT data. Most importantly, this article reveals that previous methods of estimatIng mInimum In-Situ Stress often lead to significant over or underestimates. Based on our modelIng and simulation results, we propose a much more accurate and reliable method to estimate the mInimum In-Situ Stress and fracture pressure dependent leak-off rate.
Shahab D. Mohaghegh - One of the best experts on this subject based on the ideXlab platform.
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DetermInIng In-Situ Stress Profiles From Logs
SPE Annual Technical Conference and Exhibition, 2004Co-Authors: Shahab D. Mohaghegh, Andrei Popa, Razi Gaskari, S. Wolhart, R. Siegfreid, Samuel AmeriAbstract:This paper presents a new and novel technique for determInIng the In-Situ Stress profile of hydrocarbon reservoirs from geophysical well logs usIng a combInation of fuzzy logic and neural networks. It is well established, that In-Situ Stress cannot be generated from well logs alone. This is because two sets of formations may have very similar geologic signatures but possess different In-Situ Stress profiles because of varyIng degrees of tectonic activities In each region. By usIng two new parameters as surrogates for tectonic activities, fuzzy logic to Interpret the logs and rank parameter Influence, and neural networks as a mappIng tool, it has become possible to accurately generate In-Situ Stress profiles from logs. This paper demonstrates the improved performance of this new approach over conventional approaches used In the Industry.
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DetermInIng In-Situ Stress profiles of hydrocarbon reservoirs from geophysical well logs usIng Intelligent systems
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541), 2004Co-Authors: Shahab D. Mohaghegh, Andrei Popa, Razi Gaskari, S. Wolhart, B. Siegfried, Samuel AmeriAbstract:This work presents a new and novel technique for determInIng the In-Situ Stress profile of hydrocarbon reservoirs from geophysical well logs usIng a combInation of fuzzy logic and neural networks. It is well established, that In-Situ Stress cannot be generated from well logs alone. This is because two sets of formations may have very similar geologic signatures but possess different In-Situ Stress profiles because of varyIng degrees of tectonic activities In each region. By usIng two new parameters as surrogates for tectonic activities, fuzzy logic to Interpret the logs and rank parameter Influence, and neural network as a mappIng tool, it has become possible to accurately generate In-Situ Stress profiles. This paper demonstrates the superiority of this new approach over conventional approaches used In the oil and gas Industry.
Jian-xin Miao - One of the best experts on this subject based on the ideXlab platform.
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Inversion Method of In-Situ Stress and Rock Damage Characteristics In Dam Site UsIng Neural Network and Numerical Simulation—A Case Study
IEEE Access, 2020Co-Authors: Gan Li, Yu Hu, Qing-bin Li, Jian-xin MiaoAbstract:In mountaIn and ravIne region of southwest ChIna, several hydropower stations have been built In this area. It is the maIn national base for hydropower energy development, but under the Influence of geological structure and surface erosion, the In-Situ Stress environment In this area is more complex. The maIn purpose of this paper is to establish the relationship between measured In-Situ Stress data and numerical calculation by means of neural network. Therefore, it can be used to analyze the distribution characteristics of large-scale In-Situ Stress and the failure of regional geological bodies under the action of In-Situ Stress In Xiluodu area. This paper analyzes the geological conditions and the measured data of In-Situ Stress In Xiluodu area. The results show that there is obvious surface weatherIng phenomenon In this area, the Stress environment is complex. The depth has a positive impact on the level of In-Situ Stress, but the impact degree is different. The genetic algorithm-BP artificial neural networks (G-P) method is traIned by the measured In-Situ Stress data. Based on the field measurement data, neural network algorithm and numerical simulation technology, the three-dimensional In-Situ Stress field distribution characteristics of the project area are carried out. The research shows that the scheme of combInIng the actual measurement, numerical analysis and neural network Inversion is reliable; Depth is an important factor affectIng the maximum horizontal Stress value In Xiluodu area; Under the action of In-Situ Stress, the fissures of geological body are relatively developed, and three types of origInal water storage and flow spaces are formed before dam storage period; The flow and storage space of groundwater Includes limestone fracture, basalt fracture and slope fracture aquifer; After the impoundment of the reservoir area, the reservoir water is transmitted downward through the vertical fissures, and fInally the reservoir water forms a hydraulic connection with the groundwater. After impoundment, the hydrogeological conditions of the reservoir area would be changed.
