JZS oilfield is an offshore metamorphic rock fractured buried hill oilfield. It was put into development in July 2010. The overall production situation of the oilfield is good, but some problems have been exposed. The main performance is as follows: It is difficult to accurately characterize the heterogeneity of fracture space distribution; In the numerical simulation of fractured reservoir, it is impossible to accurately describe and predict the fracture flow of fluid channeling in corner point grid system. In order to solve the above problems, this study presents a new integrated fractured reservoir geological modeling and numerical simulation research method based on unstructured grid. There are three key aspects to this method. (1) The multi-scale (large, middle and small) discrete fracture system is established by combining outcrop measurement data with well point information and seismic attributes. On the basis of post-stack 3D seismic data, ants attributes are extracted, then the ant body results are transformed into large scale fractures; Using azimuth anisotropy attribute based on pre-stack inversion and combining the distribution orientation of large-scale fractures, the middle-scale fractures are established; According to the power law distribution relation between the cumulative frequency and the fracture length of large scale and small scale which based on outcrop observation, the imaging logging data and pre-stack inversion azimuth anisotropy attribute, small scale fractures are constructed by DFN technology.(2) For multi-scale fractures, the unstructured grid division technique is used to build a 3D model that conforms to the heterogeneity of dual media. In this study, a layered triangular prism grid generation technique is proposed. It is used to establish model of multi-scale fractures based on unstructured grid. Using large-scale fractures as a constraint, full 3D unstructured grid model is set up, and the discrete fracture model can accurately describe the fracture system and the coupling relationship between matrix and the fracture;(3)The triple-medium numerical simulation of the reservoir in the study area is carried out by using the automatic history fitting technology of ensemble kalman filter (EnKF). After several parameter adjustments, both the coincidence rate of the index and the fitting precision are higher than before. Multi-scale discrete fracture model based on the large-scale fractures discretization processing, equivalent medium processing to middle and small scale fractures, keeps the seepage characteristic of the large-scale discrete fractures model and ensures the calculation efficiency. The results show that the new method has obvious advantages in computing speed and that the fitting effect is closer to the actual production performance.
{"title":"Application of an Integrative New Technique on Modeling and Numerical Simulation for Fractured Reservoir Based on Unstructured Grid: A Case Study of JZS Buried Hill Reservoir","authors":"Zuobin Lv, Chunliang Huo, Lizhen Ge, Jing Xu, Zhiqiang Zhu","doi":"10.2523/IPTC-19267-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19267-MS","url":null,"abstract":"\u0000 JZS oilfield is an offshore metamorphic rock fractured buried hill oilfield. It was put into development in July 2010. The overall production situation of the oilfield is good, but some problems have been exposed. The main performance is as follows: It is difficult to accurately characterize the heterogeneity of fracture space distribution; In the numerical simulation of fractured reservoir, it is impossible to accurately describe and predict the fracture flow of fluid channeling in corner point grid system.\u0000 In order to solve the above problems, this study presents a new integrated fractured reservoir geological modeling and numerical simulation research method based on unstructured grid. There are three key aspects to this method. (1) The multi-scale (large, middle and small) discrete fracture system is established by combining outcrop measurement data with well point information and seismic attributes. On the basis of post-stack 3D seismic data, ants attributes are extracted, then the ant body results are transformed into large scale fractures; Using azimuth anisotropy attribute based on pre-stack inversion and combining the distribution orientation of large-scale fractures, the middle-scale fractures are established; According to the power law distribution relation between the cumulative frequency and the fracture length of large scale and small scale which based on outcrop observation, the imaging logging data and pre-stack inversion azimuth anisotropy attribute, small scale fractures are constructed by DFN technology.(2) For multi-scale fractures, the unstructured grid division technique is used to build a 3D model that conforms to the heterogeneity of dual media. In this study, a layered triangular prism grid generation technique is proposed. It is used to establish model of multi-scale fractures based on unstructured grid. Using large-scale fractures as a constraint, full 3D unstructured grid model is set up, and the discrete fracture model can accurately describe the fracture system and the coupling relationship between matrix and the fracture;(3)The triple-medium numerical simulation of the reservoir in the study area is carried out by using the automatic history fitting technology of ensemble kalman filter (EnKF). After several parameter adjustments, both the coincidence rate of the index and the fitting precision are higher than before.\u0000 Multi-scale discrete fracture model based on the large-scale fractures discretization processing, equivalent medium processing to middle and small scale fractures, keeps the seepage characteristic of the large-scale discrete fractures model and ensures the calculation efficiency. The results show that the new method has obvious advantages in computing speed and that the fitting effect is closer to the actual production performance.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76202731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Harris, Samita Santoshini, Stewart Smith, A. Levannier, O. H. Khan
The vast majority of grids for reservoir modeling and simulation workflows are based on pillar gridding or stairstep grid technologies. The grids are part of a feature-rich and well-established modeling workflow provided by many commercial software packages. Undesirable and significant simplifications to the gridding often arise when employing such approaches in structurally complex areas, and this will clearly lead to poor predictions from the downstream modeling. In the classical gridding and modeling workflow, the grid is built in geological space from input horizon and fault interpretations, and the property modeling occurs in an approximated ‘depositional’ space generated from the geological space grid cells. The unstructured grids that we consider here are based on a very different workflow: a volume-based structural model is first constructed from the fault/horizon input data; a flattening (‘depositional’) mapping deforms the mesh of the structural model under mechanical and geometric constraints; the property modeling occurs in this depositional space on a regular cuboidal grid; after ‘cutting’ this grid by the geological discontinuities, the inverse depositional mapping recovers the final unstructured grid in geological space. A critical part of the depositional transformation is the improved preservation of geodetic distances and the layer-orthogonality of the grid cells. The final grid is an accurate representation of the input structural model, and therefore the quality checking of the modeling workflow must be focused on the input data and structural model creation. We describe a variety of basic quality checking and structurally-focused tools that should be applied at this stage; these tools aim to ensure the accuracy of the depositional transformation, and consequently ensure both the quality of the generated grid and the consistent representation of the property models. A variety of quality assurance metrics applied to the depositional/geological grid geometries provide spatial measures of the ‘quality’ of the gridding and modeling workflow, and the ultimate validation of the structural quality of the input data. Two case studies will be used to demonstrate this novel workflow for creating high-quality unstructured grids in structurally complex areas. The improved quality is validated by monitoring downstream impacts on property prediction and reservoir simulation; these improved prediction scenarios are a more accurate basis for history matching approaches.
{"title":"Complex Geological Modeling Using Unstructured Grids: Quality Assurance Approaches and Improved Prediction","authors":"S. Harris, Samita Santoshini, Stewart Smith, A. Levannier, O. H. Khan","doi":"10.2523/IPTC-19303-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19303-MS","url":null,"abstract":"\u0000 The vast majority of grids for reservoir modeling and simulation workflows are based on pillar gridding or stairstep grid technologies. The grids are part of a feature-rich and well-established modeling workflow provided by many commercial software packages. Undesirable and significant simplifications to the gridding often arise when employing such approaches in structurally complex areas, and this will clearly lead to poor predictions from the downstream modeling.\u0000 In the classical gridding and modeling workflow, the grid is built in geological space from input horizon and fault interpretations, and the property modeling occurs in an approximated ‘depositional’ space generated from the geological space grid cells. The unstructured grids that we consider here are based on a very different workflow: a volume-based structural model is first constructed from the fault/horizon input data; a flattening (‘depositional’) mapping deforms the mesh of the structural model under mechanical and geometric constraints; the property modeling occurs in this depositional space on a regular cuboidal grid; after ‘cutting’ this grid by the geological discontinuities, the inverse depositional mapping recovers the final unstructured grid in geological space. A critical part of the depositional transformation is the improved preservation of geodetic distances and the layer-orthogonality of the grid cells.\u0000 The final grid is an accurate representation of the input structural model, and therefore the quality checking of the modeling workflow must be focused on the input data and structural model creation. We describe a variety of basic quality checking and structurally-focused tools that should be applied at this stage; these tools aim to ensure the accuracy of the depositional transformation, and consequently ensure both the quality of the generated grid and the consistent representation of the property models. A variety of quality assurance metrics applied to the depositional/geological grid geometries provide spatial measures of the ‘quality’ of the gridding and modeling workflow, and the ultimate validation of the structural quality of the input data.\u0000 Two case studies will be used to demonstrate this novel workflow for creating high-quality unstructured grids in structurally complex areas. The improved quality is validated by monitoring downstream impacts on property prediction and reservoir simulation; these improved prediction scenarios are a more accurate basis for history matching approaches.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76628224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Structural dip is the term used in borehole image and dipmeter interpretation to indicate the "tectonic" tilting in the vicinity of the wellbore. Structural dip, by definition, is the formation dip component that is caused by tectonic deformation such as folding, faulting, uplift and others. Knowledge of the structural dip in the vicinity of the borehole is essential for several applications, including field structural modeling, well placement, geosteering of the lateral sections, and seismic data processing. Traditionally, structural dip is computed from borehole image data using laminated shale dip based on the assumption that the laminated shale was deposited out of suspension and that the lamination was originally deposited as horizontal beds. This means that any tilting observed in laminated shale with "coherent" lamination is caused by tectonic tilting; hence, it can be used to compute the structural dip. There is nearly a consensus in the industry around this assumption, and the laminated shale dip is widely used to compute structural dip. There are several geological settings under which laminated shale can form. Those are mostly subaqueous setting such as marine and lacustrine settings. Drilling through rocks deposited in such settings normally encounters sequences of laminated shale from which structural dip can be computed. However, rock formations deposited in subaerial environments often lacks settings under which laminated shale forms. Such environments are often dominated by sandstone lithologies deposited in high- energy settings this rich in sedimentary structures such as crossbedding. Due to absence of laminated shale sequences, computation of structural dip using the traditional approach is not possible. This paper explains a technique that can be used to estimate structural dip from cross bedding on borehole images. It uses the geometrical relationship between the crossbedding surfaces and the lower set boundary of the corresponding crossbedding set. The line of intersection between these two surfaces is assumed to be horizontal at the time of deposition. Measuring multiple lines of intersections, plotting them on a stereonet, and fitting a great circle to them helps estimate the structural dip within the analyzed interval. The best- fitting great circle of these lines is believed to be a reasonable estimation of the structural dip. This approach has been tested on few image log datasets with cross bedded sandstone facies and proved to be very close to the actual structural dip computation obtained from the shale facies in the same depositional sequence. This paper will illustrate some interpreted image log supporting this technique.
{"title":"Structural Dip Estimation from Crossbedding on Borehole Images","authors":"G. Sultan, Walid Jibreel","doi":"10.2523/IPTC-19309-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19309-MS","url":null,"abstract":"\u0000 Structural dip is the term used in borehole image and dipmeter interpretation to indicate the \"tectonic\" tilting in the vicinity of the wellbore. Structural dip, by definition, is the formation dip component that is caused by tectonic deformation such as folding, faulting, uplift and others.\u0000 Knowledge of the structural dip in the vicinity of the borehole is essential for several applications, including field structural modeling, well placement, geosteering of the lateral sections, and seismic data processing.\u0000 Traditionally, structural dip is computed from borehole image data using laminated shale dip based on the assumption that the laminated shale was deposited out of suspension and that the lamination was originally deposited as horizontal beds. This means that any tilting observed in laminated shale with \"coherent\" lamination is caused by tectonic tilting; hence, it can be used to compute the structural dip. There is nearly a consensus in the industry around this assumption, and the laminated shale dip is widely used to compute structural dip.\u0000 There are several geological settings under which laminated shale can form. Those are mostly subaqueous setting such as marine and lacustrine settings. Drilling through rocks deposited in such settings normally encounters sequences of laminated shale from which structural dip can be computed. However, rock formations deposited in subaerial environments often lacks settings under which laminated shale forms. Such environments are often dominated by sandstone lithologies deposited in high- energy settings this rich in sedimentary structures such as crossbedding. Due to absence of laminated shale sequences, computation of structural dip using the traditional approach is not possible.\u0000 This paper explains a technique that can be used to estimate structural dip from cross bedding on borehole images. It uses the geometrical relationship between the crossbedding surfaces and the lower set boundary of the corresponding crossbedding set. The line of intersection between these two surfaces is assumed to be horizontal at the time of deposition. Measuring multiple lines of intersections, plotting them on a stereonet, and fitting a great circle to them helps estimate the structural dip within the analyzed interval. The best- fitting great circle of these lines is believed to be a reasonable estimation of the structural dip.\u0000 This approach has been tested on few image log datasets with cross bedded sandstone facies and proved to be very close to the actual structural dip computation obtained from the shale facies in the same depositional sequence. This paper will illustrate some interpreted image log supporting this technique.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82675097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Creating Chan water control diagnostic plots is a common well surveillance activity to search for signatures that distinguish and explain mechanisms behind excessive water production in oil wells. The technique involves an engineer who visually classifies patterns or signatures related to a water production mechanism. This study shows how the Chan plot signature identification can be approached as a machine learning (ML) classification problem, where a well can be characterized by the slopes of water-oil ratio (WOR) and WOR time derivative (WOR’) curves. A model tries to find the pattern category to which that well belongs. Having ML models that can predict whether a well belongs to a specific Chan plot signature, or pattern, would be valuable as a well surveillance tool, especially in high-well-count fields. Our previous work focused on using the shape of the Chan plot as features for a radial basis function (RBF) support vector machines (SVM) model. In this study, we examine how features to identify Chan plot signatures can be simplified and how different ML models compare in accuracy. ML models used in this study were: nearest neighbor, SVM, decision tree, random forest, logistic regression, and Naive Bayes. In this study, we use the slopes of WOR and WOR’ as features. As a result, we observed an increase in the accuracy of the ML models that we used. By performing the quality check on the data set after selecting slopes as features, we identified that the dataset contained several incorrectly labeled examples, which we adjusted before we trained the ML models. By comparing the models’ metrics in the context of the test set, we identified that the ML model with the highest f1-score was nearest neighbor at 0.93, whereas the RBF SVM model achieved a value of 0.90. We also compared models’ decision boundaries to find how they differ among all ML models. We obtained an improved accuracy of an ML model by simplifying features as well as raising the quality of data used in the Chan plot signature identification problem. These ML models could be useful in automatic classification whether a well exhibits a specific Chan plot signature, to flag it for a review within a broader petroleum engineering decision framework.
{"title":"Chan Plot Signature Identification as a Practical Machine Learning Classification Problem","authors":"C. A. Garcia, A. Mukhanov, Henry Torres","doi":"10.2523/IPTC-19143-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19143-MS","url":null,"abstract":"\u0000 Creating Chan water control diagnostic plots is a common well surveillance activity to search for signatures that distinguish and explain mechanisms behind excessive water production in oil wells. The technique involves an engineer who visually classifies patterns or signatures related to a water production mechanism. This study shows how the Chan plot signature identification can be approached as a machine learning (ML) classification problem, where a well can be characterized by the slopes of water-oil ratio (WOR) and WOR time derivative (WOR’) curves. A model tries to find the pattern category to which that well belongs. Having ML models that can predict whether a well belongs to a specific Chan plot signature, or pattern, would be valuable as a well surveillance tool, especially in high-well-count fields.\u0000 Our previous work focused on using the shape of the Chan plot as features for a radial basis function (RBF) support vector machines (SVM) model. In this study, we examine how features to identify Chan plot signatures can be simplified and how different ML models compare in accuracy. ML models used in this study were: nearest neighbor, SVM, decision tree, random forest, logistic regression, and Naive Bayes. In this study, we use the slopes of WOR and WOR’ as features. As a result, we observed an increase in the accuracy of the ML models that we used. By performing the quality check on the data set after selecting slopes as features, we identified that the dataset contained several incorrectly labeled examples, which we adjusted before we trained the ML models. By comparing the models’ metrics in the context of the test set, we identified that the ML model with the highest f1-score was nearest neighbor at 0.93, whereas the RBF SVM model achieved a value of 0.90. We also compared models’ decision boundaries to find how they differ among all ML models.\u0000 We obtained an improved accuracy of an ML model by simplifying features as well as raising the quality of data used in the Chan plot signature identification problem. These ML models could be useful in automatic classification whether a well exhibits a specific Chan plot signature, to flag it for a review within a broader petroleum engineering decision framework.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85840163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weixu Wang, H. Wen, Pei Jiang, Pengwei Zhang, Z. Lei, Chenggang Xian, Junjun Li, Chunduan Zhao, Qingshan Li, Qinghui Xie
The shale gas in Jingmen area in China has unique features different from North America shale plays, such as abundant natural fracture corridors with complex patterns and distributions, formed through multiple tectonics in geological history, high in-situ stresses with extreme variations of heterogeneities and anisotropies, and highly laminated rocks. Wells drilled in this area are often less stable than comparable wells drilled into non-laminated rocks. Hydraulic fracturing has encountered many difficulties, such as high treating pressure, difficulty in proppant placement, constrained fracture height and complex fracture geometry. It has been recognized that optimizing lateral landing and wellbore trajectory is essential to reduce operation risks and improve productivities. An integrated 3D shared earth model was constructed with 0.5-m vertical resolution of the targeted sweet section to capture vertical heterogeneities measured from logs through integrating seismic, geological structure, log, and core data. This model includes anisotropic mechanical properties, in-situ stress field, and multiscale natural fracture systems. Near borehole induced stress was computed accounting formation anisotropies, and wellbore shear failure mechanism was modeled by a modified Plane of Weakness (PoW) model. The model can predict the extent of failure region around the wellbore and then provide mud weight window for safe and effective drilling. The fracturing simulations were performed with Unconventional Fracture Model (UFM) that models the hydraulic fracturing process in complex formations with pre-existing natural fractures including interaction with natural fractures and between hydraulic fracture branches (i.e., stress shadow effects). Numerical reservoir simulations were computed to forecast productivities of different lateral landing and well trajectory designs and provide optimal strategy. A comprehensive integrated workflow was generated from drilling to production through stimulation to optimize well planning. This study proposed the best interval L111 for lateral placement and optimal well trajectory along NE23° for wellbore stability and hydraulic fracturing effectiveness to reduce operation risks and ahicheve highest productivities considering unevenly well-developed natural fractures, significant heterogenetic and anisotropic in-situ stress, Guanyinqiao limestone formation and highly laminated rock. This integrated workflow represents the comprehensive multidisciplinary approach to coupling geophysics, geology, petrophysics, geomechanics, wellbore stability, complex hydraulic fracture propagation, and production simulation models aimed towards optimizing lateral landing and well trajectory. The implementation of this workflow guides drilling, stimulation and development of shale gas reservoirs in the most optimized and scientific way.
{"title":"Application of Anisotropic Wellbore Stability Model and Unconventional Fracture Model for Lateral Landing and Wellbore Trajectory Optimization: A Case Study of Shale Gas in Jingmen Area, China","authors":"Weixu Wang, H. Wen, Pei Jiang, Pengwei Zhang, Z. Lei, Chenggang Xian, Junjun Li, Chunduan Zhao, Qingshan Li, Qinghui Xie","doi":"10.2523/IPTC-19368-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19368-MS","url":null,"abstract":"\u0000 The shale gas in Jingmen area in China has unique features different from North America shale plays, such as abundant natural fracture corridors with complex patterns and distributions, formed through multiple tectonics in geological history, high in-situ stresses with extreme variations of heterogeneities and anisotropies, and highly laminated rocks. Wells drilled in this area are often less stable than comparable wells drilled into non-laminated rocks. Hydraulic fracturing has encountered many difficulties, such as high treating pressure, difficulty in proppant placement, constrained fracture height and complex fracture geometry. It has been recognized that optimizing lateral landing and wellbore trajectory is essential to reduce operation risks and improve productivities.\u0000 An integrated 3D shared earth model was constructed with 0.5-m vertical resolution of the targeted sweet section to capture vertical heterogeneities measured from logs through integrating seismic, geological structure, log, and core data. This model includes anisotropic mechanical properties, in-situ stress field, and multiscale natural fracture systems. Near borehole induced stress was computed accounting formation anisotropies, and wellbore shear failure mechanism was modeled by a modified Plane of Weakness (PoW) model. The model can predict the extent of failure region around the wellbore and then provide mud weight window for safe and effective drilling. The fracturing simulations were performed with Unconventional Fracture Model (UFM) that models the hydraulic fracturing process in complex formations with pre-existing natural fractures including interaction with natural fractures and between hydraulic fracture branches (i.e., stress shadow effects). Numerical reservoir simulations were computed to forecast productivities of different lateral landing and well trajectory designs and provide optimal strategy.\u0000 A comprehensive integrated workflow was generated from drilling to production through stimulation to optimize well planning. This study proposed the best interval L111 for lateral placement and optimal well trajectory along NE23° for wellbore stability and hydraulic fracturing effectiveness to reduce operation risks and ahicheve highest productivities considering unevenly well-developed natural fractures, significant heterogenetic and anisotropic in-situ stress, Guanyinqiao limestone formation and highly laminated rock.\u0000 This integrated workflow represents the comprehensive multidisciplinary approach to coupling geophysics, geology, petrophysics, geomechanics, wellbore stability, complex hydraulic fracture propagation, and production simulation models aimed towards optimizing lateral landing and well trajectory. The implementation of this workflow guides drilling, stimulation and development of shale gas reservoirs in the most optimized and scientific way.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86573503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qingzhong Zhu, Yanhui Yang, Longwei Chen, Yuting Wang, B. Chen, Chunli Liu, Chen Zhang, Xiaoxuan Wang
In order to solve the problems of poor adaptability of reservoir stimulation technology and low gas production of single well in high-rank coalbed methane (CBM) reservoir, a new concept of "methane-leading" reservoir stimulation technology and the corresponding technology method system are put forward. The concept of "methane-leading" reservoir stimulation technology emphasizes the complexity of the coal reservoir and the energy releasing process in the coalbed methane development. Through targeted artificial stimulation, a multi-stage interconnected fracture network system is built to reduce seepage resistance and finally improve the gas production of single well. The characteristics of coal reservoir and problems of traditional stimulation technology are analyzed in this paper. And the "methane-leading" reservoir stimulation technology focus on the optimization of the "sweet section", the release of injected energy and the expansion of area stimulated by the fracture network. The application results in the CBM field in the south of Qinshui basin, Shanxi Province, China, shows that the gas production of a single vertical well is more than twice that of an old well in the same area, reaching 2500~3000 m3/d and the average gas production per horizontal well is over 10000 m3/d, indicating a good application prospect. The innovation of this paper lies in that a new concept of "methane-leading" reservoir stimulation technology and the corresponding technology method with CBM characteristics are put forward. It provides new ideas and methods for effectively improving the gas production capacity of CBM single well, realizing efficient development of high-rank CBM and promoting the healthy development of CBM industry.
{"title":"Exploration and Practice of Methane-Leading Reservoir Stimulation Technology of High-Rank Coalbed Methane","authors":"Qingzhong Zhu, Yanhui Yang, Longwei Chen, Yuting Wang, B. Chen, Chunli Liu, Chen Zhang, Xiaoxuan Wang","doi":"10.2523/IPTC-19229-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19229-MS","url":null,"abstract":"\u0000 In order to solve the problems of poor adaptability of reservoir stimulation technology and low gas production of single well in high-rank coalbed methane (CBM) reservoir, a new concept of \"methane-leading\" reservoir stimulation technology and the corresponding technology method system are put forward. The concept of \"methane-leading\" reservoir stimulation technology emphasizes the complexity of the coal reservoir and the energy releasing process in the coalbed methane development. Through targeted artificial stimulation, a multi-stage interconnected fracture network system is built to reduce seepage resistance and finally improve the gas production of single well. The characteristics of coal reservoir and problems of traditional stimulation technology are analyzed in this paper. And the \"methane-leading\" reservoir stimulation technology focus on the optimization of the \"sweet section\", the release of injected energy and the expansion of area stimulated by the fracture network. The application results in the CBM field in the south of Qinshui basin, Shanxi Province, China, shows that the gas production of a single vertical well is more than twice that of an old well in the same area, reaching 2500~3000 m3/d and the average gas production per horizontal well is over 10000 m3/d, indicating a good application prospect. The innovation of this paper lies in that a new concept of \"methane-leading\" reservoir stimulation technology and the corresponding technology method with CBM characteristics are put forward. It provides new ideas and methods for effectively improving the gas production capacity of CBM single well, realizing efficient development of high-rank CBM and promoting the healthy development of CBM industry.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"114 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87603143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unconventional oil and gas resources such as shale gas, shale oil, CBM, tight gas and oil have attracted more and more attention worldwide in recent years. However, most of the formations of unconventional oil and gas are suffering from poor geological condition, thus the resources can not be developed without fracturing stimulation. Conventional hydraulic fracturing usually consumes a huge amount of water and also leads to the pollutions of surface water and even residential water. In addition, the formation damage caused by incomplete gel breaking, adsorption of polymers, clay expansion and water blocking are still not fully eliminated. Thus, in this work, ultra-dry CO2 foam stabilized by graphene oxide (GO) were explored to get a fracturing fluid characterized by low water consumption, environmental friendliness, high efficiency and low formation damage. The foam quality of fracturing fluid in the study was higher than 90%, thus the water consumption of fracturing fluid was lower than 10% of total volume. The foam stability, rheology and dynamic filtration were studied by using a large-scale fracturing fluid test device. The results showed that the stability and thermal adaptability of ultra-dry CO2 foam were enhanced by the addition of graphene oxide. The interfacial dilatational viscoelastic modulus of CO2/liquid was increased when the graphene oxide was used with saponin, implying that the bubble film interface became solid-like; The ultra-dry CO2 foam enhanced by the graphene oxide showed a shear thinning behavior. The effective viscosity of ultra-dry CO2 foam was increased by adding graphene oxide and its viscosity was higher than 50 mPa·s at a shear rate of 100s-1; Moreover, compared to pure surfactant foam, the filtration control performance of ultra-dry CO2 foam was also enhanced by graphene oxide. At a filtration pressure difference of 3.5MPa, the filtration coefficient of ultra-dry CO2 foam was decreased significantly by the addition of graphene oxide. Although the core damage caused by foam with graphene oxide was slightly higher than that of pure surfactant foam, the permeability damage was still below 10%, implying that the foam as a fracturing fluid is relatively clean to formation. Ultra-dry CO2 foam fracturing fluid stabilized by graphene oxide provides a new high-performance fracturing system for unconventional oil and gas at water-deficient area. This study will be beneficial to fracturing applications characterized by low water consumption, environmental friendliness, high efficiency and low formation damage.
{"title":"Study of Ultra-Dry CO2 Foam Fracturing Fluid Enhanced By Graphene Oxide","authors":"Qichao Lv, Zhaomin Li, Rong Zheng","doi":"10.2523/IPTC-19295-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19295-MS","url":null,"abstract":"\u0000 Unconventional oil and gas resources such as shale gas, shale oil, CBM, tight gas and oil have attracted more and more attention worldwide in recent years. However, most of the formations of unconventional oil and gas are suffering from poor geological condition, thus the resources can not be developed without fracturing stimulation. Conventional hydraulic fracturing usually consumes a huge amount of water and also leads to the pollutions of surface water and even residential water. In addition, the formation damage caused by incomplete gel breaking, adsorption of polymers, clay expansion and water blocking are still not fully eliminated.\u0000 Thus, in this work, ultra-dry CO2 foam stabilized by graphene oxide (GO) were explored to get a fracturing fluid characterized by low water consumption, environmental friendliness, high efficiency and low formation damage. The foam quality of fracturing fluid in the study was higher than 90%, thus the water consumption of fracturing fluid was lower than 10% of total volume. The foam stability, rheology and dynamic filtration were studied by using a large-scale fracturing fluid test device.\u0000 The results showed that the stability and thermal adaptability of ultra-dry CO2 foam were enhanced by the addition of graphene oxide. The interfacial dilatational viscoelastic modulus of CO2/liquid was increased when the graphene oxide was used with saponin, implying that the bubble film interface became solid-like; The ultra-dry CO2 foam enhanced by the graphene oxide showed a shear thinning behavior. The effective viscosity of ultra-dry CO2 foam was increased by adding graphene oxide and its viscosity was higher than 50 mPa·s at a shear rate of 100s-1; Moreover, compared to pure surfactant foam, the filtration control performance of ultra-dry CO2 foam was also enhanced by graphene oxide. At a filtration pressure difference of 3.5MPa, the filtration coefficient of ultra-dry CO2 foam was decreased significantly by the addition of graphene oxide. Although the core damage caused by foam with graphene oxide was slightly higher than that of pure surfactant foam, the permeability damage was still below 10%, implying that the foam as a fracturing fluid is relatively clean to formation.\u0000 Ultra-dry CO2 foam fracturing fluid stabilized by graphene oxide provides a new high-performance fracturing system for unconventional oil and gas at water-deficient area. This study will be beneficial to fracturing applications characterized by low water consumption, environmental friendliness, high efficiency and low formation damage.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83583968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rapid development of intelligent machinery is expected to be foundational to prospective evolution of Industry 4.0, especially for traditional industries such as the energy sector. Nanodevices, context-aware sensors, and advanced forms of robotics are expected to formulate fully autonomous cyber-physical systems capable of replacing contemporary human-operated machinery used to perform significant construction activities in hydrocarbon facilities projects. For instance, oil & gas pipeline construction projects may transform into autonomous processes through means of such intelligent cyber-physical machines leveraging contextual awareness, data mining, and analytics techniques. Such projects typically present production lifecycle vectors comprising of material procurement, logistics, and customer demand, in consistency with typical Industry 4.0 business structuring. The intelligence introduced within such vectors present significant impacts on cybersecurity factors, including production integrity, availability, and relevant confidentiality. In this paper, we study influencing factors of cybersecurity on prospective Industry 4.0's main subjects: Industrial Internet of Things (IIoT), extending to those playing role in hydrocarbon construction management. We present the status quo in IIoT cybersecurity challenges and mitigations mechanisms and strategies, in sync with potential developments of advanced cyber-physical industrial machines. The relationship of prospective IIoT advances in tandem with possible cybersecurity challenges is explored. Consequently, a gap analysis is conducted to highlight essential cybersecurity controls and whether they are already present or to be developed. We use identified gaps as engineering elements for a suggested Identity and Access Management (IAM) framework capable of: devising appropriate physical and logical controls, meeting predefined business risk profile, and assuring compliance with state or industrial compliance criteria. To qualitatively ensure validity of the framework, we draw similarity of cybersecurity challenges from similar manufacturing disciplines - to infer applicability, and apply our framework to similar challenges in these industries. We ultimately conclude effectiveness of IAM as an enabler safeguard of Industry 4.0 against relevant cybersecurity issues. The summary of our research results is presented as follows: an inventory of major categories of risks applicable to Industry 4.0 cyber-physical subjects, potential gaps in relevant cybersecurity controls, and an IAM framework made of factors designed to address the associated risks. We present a set of effectively implementable blueprints of the IAM framework developed using the Open Group Architecture Framework (TOGAF) technique, a premier methodology in the enterprise architecture modeling. Novelty of our work is primarily stemmed from the idea of targeting the hydrocarbon construction management domain with firm forms of cyber-physic
{"title":"A Cybersecurity Prospective on Industry 4.0: Enabler Role of Identity and Access Management","authors":"Osama A. Alsaadoun","doi":"10.2523/IPTC-19072-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19072-MS","url":null,"abstract":"\u0000 Rapid development of intelligent machinery is expected to be foundational to prospective evolution of Industry 4.0, especially for traditional industries such as the energy sector. Nanodevices, context-aware sensors, and advanced forms of robotics are expected to formulate fully autonomous cyber-physical systems capable of replacing contemporary human-operated machinery used to perform significant construction activities in hydrocarbon facilities projects. For instance, oil & gas pipeline construction projects may transform into autonomous processes through means of such intelligent cyber-physical machines leveraging contextual awareness, data mining, and analytics techniques. Such projects typically present production lifecycle vectors comprising of material procurement, logistics, and customer demand, in consistency with typical Industry 4.0 business structuring. The intelligence introduced within such vectors present significant impacts on cybersecurity factors, including production integrity, availability, and relevant confidentiality.\u0000 In this paper, we study influencing factors of cybersecurity on prospective Industry 4.0's main subjects: Industrial Internet of Things (IIoT), extending to those playing role in hydrocarbon construction management. We present the status quo in IIoT cybersecurity challenges and mitigations mechanisms and strategies, in sync with potential developments of advanced cyber-physical industrial machines. The relationship of prospective IIoT advances in tandem with possible cybersecurity challenges is explored. Consequently, a gap analysis is conducted to highlight essential cybersecurity controls and whether they are already present or to be developed. We use identified gaps as engineering elements for a suggested Identity and Access Management (IAM) framework capable of: devising appropriate physical and logical controls, meeting predefined business risk profile, and assuring compliance with state or industrial compliance criteria. To qualitatively ensure validity of the framework, we draw similarity of cybersecurity challenges from similar manufacturing disciplines - to infer applicability, and apply our framework to similar challenges in these industries. We ultimately conclude effectiveness of IAM as an enabler safeguard of Industry 4.0 against relevant cybersecurity issues.\u0000 The summary of our research results is presented as follows: an inventory of major categories of risks applicable to Industry 4.0 cyber-physical subjects, potential gaps in relevant cybersecurity controls, and an IAM framework made of factors designed to address the associated risks. We present a set of effectively implementable blueprints of the IAM framework developed using the Open Group Architecture Framework (TOGAF) technique, a premier methodology in the enterprise architecture modeling.\u0000 Novelty of our work is primarily stemmed from the idea of targeting the hydrocarbon construction management domain with firm forms of cyber-physic","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"488 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83417797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Capillary pressure and relative permeability are the two main factors determining the multiphase flow in oil and gas reservoirs. Dynamic capillarity, which includes the dynamic capillary pressure and the dynamic relative permeability, should be considered when performing waterflooding in low permeability oil reservoirs. To stimulate the production, hydraulic fracturing has been applied in low permeability oil reservoirs. In this work, dynamic capillarity in fractured low permeability reservoirs were investigated through numerical simulation, which applied the capillary pressure and relative permeability data obtained from steady and dynamic waterflooding experiments. The numerical simulation conducted sensitive analysis using CMG. The results show that if the steady data are used in the prediction, the oil saturation reduces more evenly and more quickly, and the production capability of the reservoir is overestimated. Moreover, the production well will be predicted to breakthrough earlier, with a higher breakthrough water flow if the dynamic capillarity is neglected This work demonstrates the importance of considering dynamic capillarity in fractured low permeability reservoirs, and provides another perspective to predict the production in fractured low permeability reservoirs.
{"title":"Dynamic Capillarity During the Water Flooding Process in Fractured Low Permeability Reservoirs","authors":"Ying Li, Haitao Li, Shengnan Chen, Yu Lu, Xiaoying Li, Hongwen Luo, Chang Liu, Cui Xiaojiang","doi":"10.2523/IPTC-19068-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19068-MS","url":null,"abstract":"\u0000 Capillary pressure and relative permeability are the two main factors determining the multiphase flow in oil and gas reservoirs. Dynamic capillarity, which includes the dynamic capillary pressure and the dynamic relative permeability, should be considered when performing waterflooding in low permeability oil reservoirs. To stimulate the production, hydraulic fracturing has been applied in low permeability oil reservoirs. In this work, dynamic capillarity in fractured low permeability reservoirs were investigated through numerical simulation, which applied the capillary pressure and relative permeability data obtained from steady and dynamic waterflooding experiments. The numerical simulation conducted sensitive analysis using CMG. The results show that if the steady data are used in the prediction, the oil saturation reduces more evenly and more quickly, and the production capability of the reservoir is overestimated. Moreover, the production well will be predicted to breakthrough earlier, with a higher breakthrough water flow if the dynamic capillarity is neglected This work demonstrates the importance of considering dynamic capillarity in fractured low permeability reservoirs, and provides another perspective to predict the production in fractured low permeability reservoirs.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"2013 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86285275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rajeev Kumar, J. Zacharia, D. Yu, A. Singh, R. Talreja, A. Bandyopadhyay, S. Subbiah
The unconventional reservoirs have emerged as major hydrocarbon prospects and optimum yield from these reservoirs is dependent on two key aspects, viz. well design and hydrofracturing wherein rock mechanics inputs play key role. The Sonic Measurements at borehole condition are used to compute the rock mechanical properties like Stress profile, Young's Modulus and Poisson's Ratio. Often, these are influenced by the anisotropy of layers and variations in well deviation for same formations. In one of the fields under review, the sonic compressional slowness varied from 8us/ft. to 20us/ft. at the target depth in shale layer in different wells drilled with varying deviation through same formations. This affected the values of stress profile, Young's Modulus and Poisson's Ratio resulting in inaccurate hydro-fracture design. At higher well deviation, breakouts were frequently observed and could not be explained on the basis of compressional slowness as it suggested faster and more competent formation. Current paper showcases case studies where hole condition improved in new wells with better hydro fracturing jobs considering effect of anisotropy in Geomechanics workflow. Sonic logs in deviated wells across shale layer were verticalized using estimated Thomson parameters considering different well path through same layer and core test results. Vertical and horizontal Young's Modulus and Poisson's Ratio were estimated for shale layers with better accuracy. The horizontal tectonic strain was constrained using radial profiles of the three shear moduli obtained from the Stoneley and cross-dipole sonic logs at depth intervals where stress induced anisotropy can be observed in permeable sandstone layer. A rock mechanics model was prepared by history matching borehole failures, drilling events and hydro-frac results in vertical and horizontal wells using updated rock properties. Geomechanical model with corrected sonic data helped to explain the breakouts in shale layer at 60deg-85deg well deviation where the original sonic basic data suggested faster and more competent formation with slight variation in stress profile among shale-sand layer. Considering shear failure, the mud weight to maintain good hole conditions at 80deg should be 0.6ppg-0.8ppg higher than that being used in offset vertical wells. Estimated closure pressure and breakdown pressure showed good match with frac results in deviated wells using new workflow. There was difference of .03psi/ft-0.07psi/ft. in shale layers using this new workflow which helped to explain frac height and containment during pressure history match. This paper elucidates the methodology that provides a reliable and accurate rock mechanics characterization to be used for well engineering applications. The study facilitates in safely and successfully drilling wells with lesser drilling issues and optimized frac stages.
{"title":"Utility of Sonic Anisotropic Measurements in Accurate Rock Mechanics Calculation For Hydro-Fracturing Design And Wellbore Stability Analysis In Unconventional Reservoirs","authors":"Rajeev Kumar, J. Zacharia, D. Yu, A. Singh, R. Talreja, A. Bandyopadhyay, S. Subbiah","doi":"10.2523/IPTC-19253-MS","DOIUrl":"https://doi.org/10.2523/IPTC-19253-MS","url":null,"abstract":"\u0000 The unconventional reservoirs have emerged as major hydrocarbon prospects and optimum yield from these reservoirs is dependent on two key aspects, viz. well design and hydrofracturing wherein rock mechanics inputs play key role. The Sonic Measurements at borehole condition are used to compute the rock mechanical properties like Stress profile, Young's Modulus and Poisson's Ratio. Often, these are influenced by the anisotropy of layers and variations in well deviation for same formations. In one of the fields under review, the sonic compressional slowness varied from 8us/ft. to 20us/ft. at the target depth in shale layer in different wells drilled with varying deviation through same formations. This affected the values of stress profile, Young's Modulus and Poisson's Ratio resulting in inaccurate hydro-fracture design. At higher well deviation, breakouts were frequently observed and could not be explained on the basis of compressional slowness as it suggested faster and more competent formation. Current paper showcases case studies where hole condition improved in new wells with better hydro fracturing jobs considering effect of anisotropy in Geomechanics workflow. Sonic logs in deviated wells across shale layer were verticalized using estimated Thomson parameters considering different well path through same layer and core test results. Vertical and horizontal Young's Modulus and Poisson's Ratio were estimated for shale layers with better accuracy. The horizontal tectonic strain was constrained using radial profiles of the three shear moduli obtained from the Stoneley and cross-dipole sonic logs at depth intervals where stress induced anisotropy can be observed in permeable sandstone layer. A rock mechanics model was prepared by history matching borehole failures, drilling events and hydro-frac results in vertical and horizontal wells using updated rock properties. Geomechanical model with corrected sonic data helped to explain the breakouts in shale layer at 60deg-85deg well deviation where the original sonic basic data suggested faster and more competent formation with slight variation in stress profile among shale-sand layer. Considering shear failure, the mud weight to maintain good hole conditions at 80deg should be 0.6ppg-0.8ppg higher than that being used in offset vertical wells. Estimated closure pressure and breakdown pressure showed good match with frac results in deviated wells using new workflow. There was difference of .03psi/ft-0.07psi/ft. in shale layers using this new workflow which helped to explain frac height and containment during pressure history match. This paper elucidates the methodology that provides a reliable and accurate rock mechanics characterization to be used for well engineering applications. The study facilitates in safely and successfully drilling wells with lesser drilling issues and optimized frac stages.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81423259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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