Plunger lift has been widely used in unconventional gas wells to remove liquid accumulation from the well.. Production surveillance provides large amount of data of production process and normal and abnormal operations, which can be used in machine learning (ML) and Artificial Intelligence (AI) to develop algorithms for anomaly diagnosis and operation optimization. However, in the surveillance data the majority is related to daily operation and the data of failure cases are rare. Also the failure cases may not be repeatable and many failure case signatures are not available until they happen. Large data size of anomaly cases are needed to improve the ML model accuracy. Dynamic simulation of the plunger lift process offers an alternative way to generate synthetic data on the specified anomalies to be used to train the ML model. It also helps better understand the trends reflected in the surveillance data and their root causes. From the available surveillance data of gas wells equipped with plunger lift, the simultaneous measurements of different parameters at different points in a production system with normal and abnormal occurrences can be analyzed and the correspondent trends/signatures can be identified. The typical signatures that conform to pre-determined anomalous patterns can be obtained. Using a commercial transient multiphase flow simulator, the actual field data of tubing/casing pressures can be matched through a tuning process. Trial-and-error is needed to improve the dynamic plunger lift model so that a good agreement with the production data can be achieved by adjusting the reservoir performance, plunger parameters or surface pipeline boundary conditions. Following the validation under different flow conditions, synthetic datasets for various operational and flow conditions can be generated by performing parametric studies. Unlike the field data, the synthetic data from the dynamic simulations mainly comprise anomaly signatures (e.g. tubing rupture, missed arrival of plunger, etc.), which can be added to the ML data pool to reduce the data covariance and increase independency.
{"title":"Improved Data Mining for Production Diagnosis of Gas Wells with Plunger Lift through Dynamic Simulations","authors":"Jianjun Zhu, Guangqiang Cao, Wei Tian, Qingqi Zhao, Haiwen Zhu, Jie Song, Jianlin Peng, Zimo Lin, Hong-quan Zhang","doi":"10.2118/196201-ms","DOIUrl":"https://doi.org/10.2118/196201-ms","url":null,"abstract":"\u0000 Plunger lift has been widely used in unconventional gas wells to remove liquid accumulation from the well.. Production surveillance provides large amount of data of production process and normal and abnormal operations, which can be used in machine learning (ML) and Artificial Intelligence (AI) to develop algorithms for anomaly diagnosis and operation optimization. However, in the surveillance data the majority is related to daily operation and the data of failure cases are rare. Also the failure cases may not be repeatable and many failure case signatures are not available until they happen. Large data size of anomaly cases are needed to improve the ML model accuracy. Dynamic simulation of the plunger lift process offers an alternative way to generate synthetic data on the specified anomalies to be used to train the ML model. It also helps better understand the trends reflected in the surveillance data and their root causes.\u0000 From the available surveillance data of gas wells equipped with plunger lift, the simultaneous measurements of different parameters at different points in a production system with normal and abnormal occurrences can be analyzed and the correspondent trends/signatures can be identified. The typical signatures that conform to pre-determined anomalous patterns can be obtained. Using a commercial transient multiphase flow simulator, the actual field data of tubing/casing pressures can be matched through a tuning process. Trial-and-error is needed to improve the dynamic plunger lift model so that a good agreement with the production data can be achieved by adjusting the reservoir performance, plunger parameters or surface pipeline boundary conditions. Following the validation under different flow conditions, synthetic datasets for various operational and flow conditions can be generated by performing parametric studies. Unlike the field data, the synthetic data from the dynamic simulations mainly comprise anomaly signatures (e.g. tubing rupture, missed arrival of plunger, etc.), which can be added to the ML data pool to reduce the data covariance and increase independency.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"96 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75825143","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}
H. Quintero, A. Abedini, M. Mattucci, Bill O’Neil, R. Wüst, Robert Hawkes, T. D. Hass, A. Toor
For optimizing and enhancing hydrocarbon recovery from unconventional plays, the technological race is currently focused on development and production of state-of-the-art surfactants that reduce interfacial tension to mitigate obstructive capillary forces and thus increase the relative permeability to hydrocarbon (kro). This study provides insight into the pore-scale evaluation of the latest flowback enhancer technologies currently applied in the Permian Basin, Texas, USA. A multidisciplinary approach, including concepts of nanotechnology, was used to assess fluid-fluid and rock-fluid interactions occurring at the nanopore scale and their implications on enhancing oil recovery. A heterogeneous dual-porosity dual-permeability microfluidic chip was designed and developed with pore geometries representing shale formations. This micro-chip simulated Wolfcamp shale with two distinct regions: (i) a high-permeability fracture zone (20 µm pore size) interconnected to (ii) a low-permeability nano-network zone (100 nm size). The fluorescent microscopy technique was applied to visualize and quantify the performance of different flowback enhancers during injection and flowback processes. This study highlights results from the nanofluidic analysis performed on Wolfcamp Formation rock specimens using a microreservoir-on-a-chip, which showed the benefits of the multi-functionalized surfactant (MFS) in terms of enhancing oil/condensate production. Test results obtained at a simulated reservoir temperature of 113°F (45°C) and a testing pressure of 2,176 psi (15 MPa) showed a significant improvement in relative permeability to hydrocarbon (kro) in the nanomodel when MFS was added to the stimulation fluids at loadings as low as 0.05% v/v. The results were compared against other premium flowback enhancers. Measurements using a high-resolution spinning drop tensiometer showed a 40-fold reduction in interfacial tension when the stimulation fluid containing MFS was tested against Wolfcamp crude at 113°F (45°C). Also, MFS outperformed other premium surfactants in Amott spontaneous imbibition analysis when tested with Wolfcamp core samples. This work used a nanofluidic model that appropriately reflected the inherent nanoconfinement of shale/tight formation to resolve the flowback process in hydraulic fracturing, and it is the first of its kind to visualize the mechanism behind this process at nanoscale. This platform also demonstrated a cost-effective alternative to coreflood testing for evaluating the effect of chemical additives on the flowback process. Conventional lab and field data were correlated with the nanofluidic analysis.
{"title":"Nanofluidic Analysis of Flowback Enhancers for the Permian Basin: Unconventional Method for Unconventional Rock","authors":"H. Quintero, A. Abedini, M. Mattucci, Bill O’Neil, R. Wüst, Robert Hawkes, T. D. Hass, A. Toor","doi":"10.2118/195880-ms","DOIUrl":"https://doi.org/10.2118/195880-ms","url":null,"abstract":"\u0000 For optimizing and enhancing hydrocarbon recovery from unconventional plays, the technological race is currently focused on development and production of state-of-the-art surfactants that reduce interfacial tension to mitigate obstructive capillary forces and thus increase the relative permeability to hydrocarbon (kro). This study provides insight into the pore-scale evaluation of the latest flowback enhancer technologies currently applied in the Permian Basin, Texas, USA. A multidisciplinary approach, including concepts of nanotechnology, was used to assess fluid-fluid and rock-fluid interactions occurring at the nanopore scale and their implications on enhancing oil recovery.\u0000 A heterogeneous dual-porosity dual-permeability microfluidic chip was designed and developed with pore geometries representing shale formations. This micro-chip simulated Wolfcamp shale with two distinct regions: (i) a high-permeability fracture zone (20 µm pore size) interconnected to (ii) a low-permeability nano-network zone (100 nm size). The fluorescent microscopy technique was applied to visualize and quantify the performance of different flowback enhancers during injection and flowback processes.\u0000 This study highlights results from the nanofluidic analysis performed on Wolfcamp Formation rock specimens using a microreservoir-on-a-chip, which showed the benefits of the multi-functionalized surfactant (MFS) in terms of enhancing oil/condensate production. Test results obtained at a simulated reservoir temperature of 113°F (45°C) and a testing pressure of 2,176 psi (15 MPa) showed a significant improvement in relative permeability to hydrocarbon (kro) in the nanomodel when MFS was added to the stimulation fluids at loadings as low as 0.05% v/v. The results were compared against other premium flowback enhancers.\u0000 Measurements using a high-resolution spinning drop tensiometer showed a 40-fold reduction in interfacial tension when the stimulation fluid containing MFS was tested against Wolfcamp crude at 113°F (45°C). Also, MFS outperformed other premium surfactants in Amott spontaneous imbibition analysis when tested with Wolfcamp core samples.\u0000 This work used a nanofluidic model that appropriately reflected the inherent nanoconfinement of shale/tight formation to resolve the flowback process in hydraulic fracturing, and it is the first of its kind to visualize the mechanism behind this process at nanoscale. This platform also demonstrated a cost-effective alternative to coreflood testing for evaluating the effect of chemical additives on the flowback process. Conventional lab and field data were correlated with the nanofluidic analysis.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80636159","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}
Nazlı Demirer, Umut Zalluhoglu, J. Marck, Hossam Gharib, Robert Darbe
Directional drilling for hydrocarbon exploration has been challenged to become more cost-effective and consistent with fast-growing drilling operations for both offshore and onshore production areas. Autonomous directional drilling provides a solution to these challenges by providing repeatable drilling decisions for accurate well placement, improved borehole quality, and flexibility to adapt smoothly to new technologies for drilling tools and sensors. This work proposes a model predictive control (MPC)-based approach for trajectory tracking in autonomous drilling. Given a well plan, bottomhole assembly (BHA) configuration, and operational drilling parameters, the optimal control problem is formulated to determine steering commands (i.e., tool face and steering ratio) necessary to achieve drilling objectives while satisfying operational constraints. The proposed control method was recently tested and validated during multiple field trials in various drilling basins on two- and three-dimensional (2D and 3D) well plans for both rotary steerable systems (RSS) and mud motors. Multiple curve sections were drilled successfully with automated steering decisions, generating smooth wellbores and maintaining proximity with the given well plan.
{"title":"A Model Predictive Control Method for Autonomous Directional Drilling","authors":"Nazlı Demirer, Umut Zalluhoglu, J. Marck, Hossam Gharib, Robert Darbe","doi":"10.2118/195917-ms","DOIUrl":"https://doi.org/10.2118/195917-ms","url":null,"abstract":"\u0000 Directional drilling for hydrocarbon exploration has been challenged to become more cost-effective and consistent with fast-growing drilling operations for both offshore and onshore production areas. Autonomous directional drilling provides a solution to these challenges by providing repeatable drilling decisions for accurate well placement, improved borehole quality, and flexibility to adapt smoothly to new technologies for drilling tools and sensors. This work proposes a model predictive control (MPC)-based approach for trajectory tracking in autonomous drilling. Given a well plan, bottomhole assembly (BHA) configuration, and operational drilling parameters, the optimal control problem is formulated to determine steering commands (i.e., tool face and steering ratio) necessary to achieve drilling objectives while satisfying operational constraints.\u0000 The proposed control method was recently tested and validated during multiple field trials in various drilling basins on two- and three-dimensional (2D and 3D) well plans for both rotary steerable systems (RSS) and mud motors. Multiple curve sections were drilled successfully with automated steering decisions, generating smooth wellbores and maintaining proximity with the given well plan.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80689348","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}
Oftentimes an organizational transformation fails not because of external reasons but internal resistance. A step often neglected by senior management in organization transformation is aligning the transformation process with the corporate culture. When a transformation works against established corporate culture, it will be rejected by the organization and will eventually fail despite the best efforts by senior management. However, if an organization transformation is closely aligned with the corporate culture, its chance of success is greatly enhanced. In this paper, we propose a step-by-step procedure to align an organization transformation process with the four layers of corporate culture. This can be pictorially illustrated by the Corporate Cultural Onion Model and the Simple Lever Model of Organizational Alignment.
{"title":"Maximizing Organizational Effectiveness by Creating a Culture of Alignment","authors":"H. Lau, Michael Pang","doi":"10.2118/196093-ms","DOIUrl":"https://doi.org/10.2118/196093-ms","url":null,"abstract":"\u0000 Oftentimes an organizational transformation fails not because of external reasons but internal resistance. A step often neglected by senior management in organization transformation is aligning the transformation process with the corporate culture. When a transformation works against established corporate culture, it will be rejected by the organization and will eventually fail despite the best efforts by senior management. However, if an organization transformation is closely aligned with the corporate culture, its chance of success is greatly enhanced. In this paper, we propose a step-by-step procedure to align an organization transformation process with the four layers of corporate culture. This can be pictorially illustrated by the Corporate Cultural Onion Model and the Simple Lever Model of Organizational Alignment.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77626931","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}
V. Krutko, B. Belozerov, S. Budennyy, E. Sadikhov, O. Kuzmina, D. Orlov, E. Muravleva, D. Koroteev
A framework for porous media topology reconstruction from petrographic thin sections for clastic rocks is proposed. The framework is based on two sequential stages: segmentation of thin sections imagesinto grains, porous media, cement (with further mineralogical classification of segmented elements) and reconstructing a three-dimensional voxel model of rock at pore scale. The framework exploits machine learning algorithms in order to segment2D thin section images, perform structural and mineralogical classification of grains, cement, pore space, and reconstruct 3D models of porous media. Segmentation of petrographic thin section images and mineral classification of the segmented objects are performed by the means of combination of image processing methods and Convolutional Neural Networks (CNNs). The 3D porous media reconstruction is done by means of the Generative Adversarial Networks (GANs) are applied to the segmented and classified 2D images of thin sections. As the criteria of the reconstruction quality, the following metrics were numerically calculated and compared for original and reconstructed synthetic 3D models of porous rocks: Minkowski functionals (porosity, surface area, mean breadth, Euler characteristic) and absolute permeability. Absolute permeability was calculated using pore network model. The 3D reconstruction framework was tested on a set of thin sections and CT tomograms of the clastic samples from the Achimovskiy formation (Western Siberia). The results showed the validity of the goodness-of-fit metrics based on Minkowski functionals for reconstruction the topology of porous media. The combined usage of CNN and GAN allowed to create a robust 3D topology reconstruction framework. The calculated poroperm characteristics are correlated with laboratory measurements of porosity and permeability. The developed algorithms of automatic feature extraction from petrographic thin sections and 3D reconstruction based on these features allow to achieve the following goals. First is the reduction of the amount of the routine work done by an expert during petrographic analysis. Second leads to the reduction of the number of expensive and time-consuming CT scannings required for each physical sample in order to perform further absolute and relative permeability calculations. The proposed method can bring the petrographic thin section and CT data analysis to a new level and significantly change traditional core experiments workflow in terms of speed, data integration and rock sample preparation.
{"title":"A New Approach To Clastic Rocks Pore-Scale Topology Reconstruction Based On Automatic Thin-Section Images and Ct Scans Analysis","authors":"V. Krutko, B. Belozerov, S. Budennyy, E. Sadikhov, O. Kuzmina, D. Orlov, E. Muravleva, D. Koroteev","doi":"10.2118/196183-ms","DOIUrl":"https://doi.org/10.2118/196183-ms","url":null,"abstract":"\u0000 A framework for porous media topology reconstruction from petrographic thin sections for clastic rocks is proposed. The framework is based on two sequential stages: segmentation of thin sections imagesinto grains, porous media, cement (with further mineralogical classification of segmented elements) and reconstructing a three-dimensional voxel model of rock at pore scale.\u0000 The framework exploits machine learning algorithms in order to segment2D thin section images, perform structural and mineralogical classification of grains, cement, pore space, and reconstruct 3D models of porous media. Segmentation of petrographic thin section images and mineral classification of the segmented objects are performed by the means of combination of image processing methods and Convolutional Neural Networks (CNNs). The 3D porous media reconstruction is done by means of the Generative Adversarial Networks (GANs) are applied to the segmented and classified 2D images of thin sections.\u0000 As the criteria of the reconstruction quality, the following metrics were numerically calculated and compared for original and reconstructed synthetic 3D models of porous rocks: Minkowski functionals (porosity, surface area, mean breadth, Euler characteristic) and absolute permeability. Absolute permeability was calculated using pore network model. The 3D reconstruction framework was tested on a set of thin sections and CT tomograms of the clastic samples from the Achimovskiy formation (Western Siberia). The results showed the validity of the goodness-of-fit metrics based on Minkowski functionals for reconstruction the topology of porous media. The combined usage of CNN and GAN allowed to create a robust 3D topology reconstruction framework. The calculated poroperm characteristics are correlated with laboratory measurements of porosity and permeability.\u0000 The developed algorithms of automatic feature extraction from petrographic thin sections and 3D reconstruction based on these features allow to achieve the following goals. First is the reduction of the amount of the routine work done by an expert during petrographic analysis. Second leads to the reduction of the number of expensive and time-consuming CT scannings required for each physical sample in order to perform further absolute and relative permeability calculations. The proposed method can bring the petrographic thin section and CT data analysis to a new level and significantly change traditional core experiments workflow in terms of speed, data integration and rock sample preparation.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73846914","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}
The spectral simulation approach is a recently developed geostatistical method of stochastic reservoir property simulation. The method has theoretical advantages over classical methods and the present work studies its practical effectiveness applied to synthetic data and real case of oil reservoirs. The study provides analysis of simulations results and describes strengths and limitations of the spectral method as well as application domain where it is most efficient. The spectral method is based on Fourier analysis of well log data and consists of three major steps: decomposition of the well logs into Fourier series, simulation of Fourier coefficients in the interwell space and reconstruction of synthetic logs at every lateral point as sum of the Fourier series. The method was implemented in a software application and was used by authors for simulation of three-dimensional reservoir properties. The effectiveness of the spectral method was studied based on simulations of continuous variables on a synthetic model. Simulations performed by the spectral method were compared to simulation results obtained on the same data by the more traditional method of sequential Gaussian simulation (SGS) provided by a commercial software. Analysis of the results from quantitative and qualitative points of view showed that the spectral method performed better at reproducing vertical non-stationarities observed in well data. Practical applicability of the spectral method was demonstrated by simulation of porosity on a real oil field model, characterized by increase of porosity along depth with higher values of porosity closer to the bottom of the simulated layer. It was shown that the spectral method handled better this type of heterogeneity and reproduced distribution of porosity along the vertical axis closer to that of well data.
{"title":"Effectiveness Study of the Spectral Approach to Geostatistical Simulation","authors":"N. Ismagilov, O. Popova, A. Trushin","doi":"10.2118/196106-ms","DOIUrl":"https://doi.org/10.2118/196106-ms","url":null,"abstract":"\u0000 The spectral simulation approach is a recently developed geostatistical method of stochastic reservoir property simulation. The method has theoretical advantages over classical methods and the present work studies its practical effectiveness applied to synthetic data and real case of oil reservoirs. The study provides analysis of simulations results and describes strengths and limitations of the spectral method as well as application domain where it is most efficient.\u0000 The spectral method is based on Fourier analysis of well log data and consists of three major steps: decomposition of the well logs into Fourier series, simulation of Fourier coefficients in the interwell space and reconstruction of synthetic logs at every lateral point as sum of the Fourier series. The method was implemented in a software application and was used by authors for simulation of three-dimensional reservoir properties.\u0000 The effectiveness of the spectral method was studied based on simulations of continuous variables on a synthetic model. Simulations performed by the spectral method were compared to simulation results obtained on the same data by the more traditional method of sequential Gaussian simulation (SGS) provided by a commercial software. Analysis of the results from quantitative and qualitative points of view showed that the spectral method performed better at reproducing vertical non-stationarities observed in well data.\u0000 Practical applicability of the spectral method was demonstrated by simulation of porosity on a real oil field model, characterized by increase of porosity along depth with higher values of porosity closer to the bottom of the simulated layer. It was shown that the spectral method handled better this type of heterogeneity and reproduced distribution of porosity along the vertical axis closer to that of well data.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86315691","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}
T. Bradley, P. H. Fjeld, Jonathan Scott, S. Ogilvie
A well was drilled into a prospective new unconventional mudstone play offshore Norway. Two of five coring runs were successful while the rest yielded little to no core recovery. Investigations attributed the poor recovery to sub-optimal coring practices, equipment failure and operational errors. Recently, the accompanying petrophysical logs and seismic data were revisited, and upon detailed investigation several unusual responses were observed to correspond with intervals of poor core recovery. Subsequent investigation of the core itself substantiated that the coring issues largely had natural causes. This understanding is being applied to two imminent coring operations and has driven selection of drilling, coring and wireline technology and procedures, in addition to informing casing design. Wireline nuclear magnetic resonance (NMR) and cross dipole acoustic data, logging whilst drilling (LWD) density (including azimuthal images), neutron porosity and resistivity was acquired over the interval of interest for standard formation evaluation purposes. This interpretation was conducted immediately after the initial drilling and showed the formation to be a series of highly porous oil bearing mudstones. However, no in depth advanced interpretation was conducted at the time. Recently, advanced analysis including high resolution log enhancement, NMR 2D porosity and saturation analysis, acoustic azimuthal anisotropy, near wellbore imaging, fracture interpretation, and borehole image interpretation were performed on the log data, and new and improved 3D seismic data was interpreted. When interpreted in detail it could be observed that unusual responses in the logs showed a close correspondence to the intervals of poor core recovery. In particular, high azimuthal anisotropy was observed, and when this was compared to the near wellbore reflection image a significant planar reflecting feature was identified which is determined to be a fault. Indications of this feature was subsequently found in seismic data. When then compared to the azimuthal density image after resolution enhancement was applied, although the image is still of too low resolution to directly image the fault, disturbed bedding was observed which is commonly associated with faulted intervals. Several core fragments proved to have extensive small-scale fracturing not noticed previously, and slickenlines were found along several larger fractures previously presumed to be drilling induced. The investigations of the log data revealed that a previously unknown sub-seismic fault was present right below the depth where coring problems were encountered. The detailed interpretation was able to determine the precise location of the fault and its extent in the formation. Knowledge of this subsequently explained the coring problems encountered and helps to optimise imminent coring in the same formation. Lessons learned and the methodology likely also applies to similar formations. In this paper we
{"title":"Overcoming Coring Challenges in a New Unconventional Play Offshore by Integration of Formation Evaluation Data","authors":"T. Bradley, P. H. Fjeld, Jonathan Scott, S. Ogilvie","doi":"10.2118/195866-ms","DOIUrl":"https://doi.org/10.2118/195866-ms","url":null,"abstract":"\u0000 A well was drilled into a prospective new unconventional mudstone play offshore Norway. Two of five coring runs were successful while the rest yielded little to no core recovery. Investigations attributed the poor recovery to sub-optimal coring practices, equipment failure and operational errors. Recently, the accompanying petrophysical logs and seismic data were revisited, and upon detailed investigation several unusual responses were observed to correspond with intervals of poor core recovery. Subsequent investigation of the core itself substantiated that the coring issues largely had natural causes. This understanding is being applied to two imminent coring operations and has driven selection of drilling, coring and wireline technology and procedures, in addition to informing casing design.\u0000 Wireline nuclear magnetic resonance (NMR) and cross dipole acoustic data, logging whilst drilling (LWD) density (including azimuthal images), neutron porosity and resistivity was acquired over the interval of interest for standard formation evaluation purposes. This interpretation was conducted immediately after the initial drilling and showed the formation to be a series of highly porous oil bearing mudstones. However, no in depth advanced interpretation was conducted at the time. Recently, advanced analysis including high resolution log enhancement, NMR 2D porosity and saturation analysis, acoustic azimuthal anisotropy, near wellbore imaging, fracture interpretation, and borehole image interpretation were performed on the log data, and new and improved 3D seismic data was interpreted. When interpreted in detail it could be observed that unusual responses in the logs showed a close correspondence to the intervals of poor core recovery. In particular, high azimuthal anisotropy was observed, and when this was compared to the near wellbore reflection image a significant planar reflecting feature was identified which is determined to be a fault. Indications of this feature was subsequently found in seismic data. When then compared to the azimuthal density image after resolution enhancement was applied, although the image is still of too low resolution to directly image the fault, disturbed bedding was observed which is commonly associated with faulted intervals. Several core fragments proved to have extensive small-scale fracturing not noticed previously, and slickenlines were found along several larger fractures previously presumed to be drilling induced.\u0000 The investigations of the log data revealed that a previously unknown sub-seismic fault was present right below the depth where coring problems were encountered. The detailed interpretation was able to determine the precise location of the fault and its extent in the formation. Knowledge of this subsequently explained the coring problems encountered and helps to optimise imminent coring in the same formation. Lessons learned and the methodology likely also applies to similar formations.\u0000 In this paper we","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84686427","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}
This paper presents a description of the technology for numerical simulation of thermal gas treatment on Bazhenov formation, taking into account features of Bazhenov formation and thermal gas treatment and assumptions of the simulator. First of all it is required to determine the following parameters: voidness (porosity), permeability, fracturing, free oil (initial oil saturation), TOC (Total Organic Carbon). And also it is important to establish dependence of the parameters on temperature and pressure. Then, the process of thermal gas treatment can be conditionally divided into several stages: Effective production of light oil from drainable (permeable) zones (miscible displacement in front of the combustion front)Involvement of zones of reservoir containing kerogen during to heat treatment (pyrolysis reaction) and liberation of light oil and gaseous hydrocarbons from "locked" zones of reservoir.Involvement of the initially non-drainable (impermeable) zones of reservoir, named matrix (doesn’t mean the same as in dual porosity/permeability system). Especially these zones are the greatest interest among reservoir engineers because it can contain huge reserves of hydrocarbons. As a result of the steps described above, a 2D model was created, a numerical realization of the key processes taking place during thermal gas treatment on Bazhenov formation was carried out. Further, the main zones characterizing the process were identified and a physical justification for the individual indicators was given. Calculations of variants involving the matrix in the drainage process were carried out. The calculated technological effect over a 50-year period of thermal gas treatment on the model (involving the production from matrix) was about 50% of the additional oil production, relative to the thermal gas treatment variant without involvement of matrix. According to the results of the work, an evaluation of the efficiency of wet combustion was carried out during thermal gas treatment. The results of the calculations clearly demonstrate the advantage of using wet combustion. It is as stimulation of production of reservoir oil, as of additional synthetic oil as a result of kerogen pyrolysis reaction.
{"title":"The Effectiveness of Thermal Gas Treatment on Bazenov Formation Using Numerical Simulation","authors":"A. Shakhmaev","doi":"10.2118/199767-stu","DOIUrl":"https://doi.org/10.2118/199767-stu","url":null,"abstract":"\u0000 This paper presents a description of the technology for numerical simulation of thermal gas treatment on Bazhenov formation, taking into account features of Bazhenov formation and thermal gas treatment and assumptions of the simulator.\u0000 First of all it is required to determine the following parameters: voidness (porosity), permeability, fracturing, free oil (initial oil saturation), TOC (Total Organic Carbon). And also it is important to establish dependence of the parameters on temperature and pressure. Then, the process of thermal gas treatment can be conditionally divided into several stages: Effective production of light oil from drainable (permeable) zones (miscible displacement in front of the combustion front)Involvement of zones of reservoir containing kerogen during to heat treatment (pyrolysis reaction) and liberation of light oil and gaseous hydrocarbons from \"locked\" zones of reservoir.Involvement of the initially non-drainable (impermeable) zones of reservoir, named matrix (doesn’t mean the same as in dual porosity/permeability system). Especially these zones are the greatest interest among reservoir engineers because it can contain huge reserves of hydrocarbons.\u0000 As a result of the steps described above, a 2D model was created, a numerical realization of the key processes taking place during thermal gas treatment on Bazhenov formation was carried out. Further, the main zones characterizing the process were identified and a physical justification for the individual indicators was given. Calculations of variants involving the matrix in the drainage process were carried out.\u0000 The calculated technological effect over a 50-year period of thermal gas treatment on the model (involving the production from matrix) was about 50% of the additional oil production, relative to the thermal gas treatment variant without involvement of matrix.\u0000 According to the results of the work, an evaluation of the efficiency of wet combustion was carried out during thermal gas treatment. The results of the calculations clearly demonstrate the advantage of using wet combustion. It is as stimulation of production of reservoir oil, as of additional synthetic oil as a result of kerogen pyrolysis reaction.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"460 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86687916","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. Penny, J. Karanikas, J. Barnett, G. Harley, Chase Hartwell, T. Waddell
Downhole electric heating has historically been unreliable or limited to short, often vertical, well sections. Technology improvements over the past several years now allow for reliable, long length, relatively high powered, downhole electric heating suitable for extended-reach horizontal wells. The application of this downhole electric heating technology in two different horizontal cold-producing heavy oil wells in Alberta is presented. The first field case study discusses the application of electric heating in a mature, depleted field as a secondary recovery method while the second case study examines a virgin heavy oil reservoir, where cold production by artificial lift was economically challenged. The completion, installation, expected and actual results of both cases studies are compared and contrasted. Both field deployments demonstrate the benefits and efficacy of applying downhole electric heating. In the case of the mature depleted field, electric heating resulted in a 4X-5X increase in oil rate, sustained over a period of close to two years. The energy ratio of the heating value of the incremental produced oil to the injected heat was slightly over 7.0. In the virgin heavy oil field, electric heating reduced the viscosity of the oil in the wellbore from time zero, which allows for higher rates of oil production along the complete length of the long horizontal lateral at higher, if desired, bottomhole pressures than in a cold-producing well. This degree of freedom may ultimately allow for an operating policy that suppresses excessive production of dissolved gas, thereby helping conserve reservoir energy. Early production data in this field show 4X-6X higher oil rates form the heated well than from the cold-producing benchmark well in the same reservoir. Numerical simulation models, which include reactions that account for the foamy nature of the produced oil and the downhole injection of heat, have been developed and calibrated against field data. The models can be used to prescribe the range of optimal reservoir and fluid properties to select the most promising targets (fields, wells) for downhole electric heating as a production optimization method, which is crucially important in the current low oil price scenario. The same models can also be used during the execution of the project to explore optimal operating conditions and operating procedures. Downhole electric heating in long horizontal wells is now a commercially available technology that can be reliably applied as a production optimization recovery scheme in heavy oil reservoirs. Understanding the optimum reservoir conditions where the application of downhole electric heating maximizes economic benefits will assist in identifying areas of opportunity to meaningfully increase reserves and production in heavy oil reservoirs in Alberta as well as around the world.
{"title":"Field Case Studies of Downhole Electric Heating in Two Horizontal Alberta Heavy Oil Wells","authors":"S. Penny, J. Karanikas, J. Barnett, G. Harley, Chase Hartwell, T. Waddell","doi":"10.2118/196187-ms","DOIUrl":"https://doi.org/10.2118/196187-ms","url":null,"abstract":"\u0000 Downhole electric heating has historically been unreliable or limited to short, often vertical, well sections. Technology improvements over the past several years now allow for reliable, long length, relatively high powered, downhole electric heating suitable for extended-reach horizontal wells. The application of this downhole electric heating technology in two different horizontal cold-producing heavy oil wells in Alberta is presented.\u0000 The first field case study discusses the application of electric heating in a mature, depleted field as a secondary recovery method while the second case study examines a virgin heavy oil reservoir, where cold production by artificial lift was economically challenged. The completion, installation, expected and actual results of both cases studies are compared and contrasted.\u0000 Both field deployments demonstrate the benefits and efficacy of applying downhole electric heating. In the case of the mature depleted field, electric heating resulted in a 4X-5X increase in oil rate, sustained over a period of close to two years. The energy ratio of the heating value of the incremental produced oil to the injected heat was slightly over 7.0. In the virgin heavy oil field, electric heating reduced the viscosity of the oil in the wellbore from time zero, which allows for higher rates of oil production along the complete length of the long horizontal lateral at higher, if desired, bottomhole pressures than in a cold-producing well. This degree of freedom may ultimately allow for an operating policy that suppresses excessive production of dissolved gas, thereby helping conserve reservoir energy. Early production data in this field show 4X-6X higher oil rates form the heated well than from the cold-producing benchmark well in the same reservoir.\u0000 Numerical simulation models, which include reactions that account for the foamy nature of the produced oil and the downhole injection of heat, have been developed and calibrated against field data. The models can be used to prescribe the range of optimal reservoir and fluid properties to select the most promising targets (fields, wells) for downhole electric heating as a production optimization method, which is crucially important in the current low oil price scenario. The same models can also be used during the execution of the project to explore optimal operating conditions and operating procedures.\u0000 Downhole electric heating in long horizontal wells is now a commercially available technology that can be reliably applied as a production optimization recovery scheme in heavy oil reservoirs. Understanding the optimum reservoir conditions where the application of downhole electric heating maximizes economic benefits will assist in identifying areas of opportunity to meaningfully increase reserves and production in heavy oil reservoirs in Alberta as well as around the world.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90282980","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}
Xuanqing Lou, Nirjhor Chakraborty, Z. Karpyn, L. Ayala, N. Nagarajan, Zein Wijaya
The design of oil recovery processes by gas injection or vapor solvent relies on knowledge of diffusion coefficients to enable meaningful production predictions. However, lab measurements of diffusion coefficients are often performed on bulk fluids, without accountability for the hindrance caused by the pore network structure and tortuosity of porous media. As such, our ability to predict effective diffusion coefficients in porous rocks is inadequate and, additional laboratory work is needed to investigate the impact of the medium itself on transport by diffusion. In addition, experimental data on multi-phase diffusion coefficients are particularly scarce for tight rocks. This study therefore proposes an experimental methodology, based on a pressure-decay technique, to measure diffusion of injected gas in oil saturated porous rocks. A diffusion experiment of gas into bulk oil (without porous medium) provides an upper limit estimation of this gas-liquid diffusion coefficient. Diffusion experiments using limestone and Bakken shale provide insight into different degrees of restriction in high permeability versus low permeability media. Two analytical models and one numerical model were implemented and compared to determine the diffusion coefficients from the time-dependent experimental pressure-decay data. These diffusion coefficients were found in agreement with literature on corresponding data, demonstrating the validity of the modeling approaches used. Results indicate considerable hindrance to diffusion in porous media relative to bulk oil and relates to the tortuosity and constrictivity of the rock matrix. The diffusion coefficient of methane in bulk oil is 3.8 × 10−9 m2/s. In our limestone sample, this diffusion coefficient drops by one order of magnitude, ranging between 1.5 to 6.5 × 10−10 m2/s and, it drops by another order of magnitude in the Bakken shale sample to 2.0 × 10−11 m2/s.
{"title":"Experimental Study of Gas-Liquid Diffusion in Porous Rocks and Bulk Fluids to Investigate the Effect of Rock Matrix Hindrance","authors":"Xuanqing Lou, Nirjhor Chakraborty, Z. Karpyn, L. Ayala, N. Nagarajan, Zein Wijaya","doi":"10.2118/195941-ms","DOIUrl":"https://doi.org/10.2118/195941-ms","url":null,"abstract":"\u0000 The design of oil recovery processes by gas injection or vapor solvent relies on knowledge of diffusion coefficients to enable meaningful production predictions. However, lab measurements of diffusion coefficients are often performed on bulk fluids, without accountability for the hindrance caused by the pore network structure and tortuosity of porous media. As such, our ability to predict effective diffusion coefficients in porous rocks is inadequate and, additional laboratory work is needed to investigate the impact of the medium itself on transport by diffusion. In addition, experimental data on multi-phase diffusion coefficients are particularly scarce for tight rocks. This study therefore proposes an experimental methodology, based on a pressure-decay technique, to measure diffusion of injected gas in oil saturated porous rocks. A diffusion experiment of gas into bulk oil (without porous medium) provides an upper limit estimation of this gas-liquid diffusion coefficient. Diffusion experiments using limestone and Bakken shale provide insight into different degrees of restriction in high permeability versus low permeability media. Two analytical models and one numerical model were implemented and compared to determine the diffusion coefficients from the time-dependent experimental pressure-decay data. These diffusion coefficients were found in agreement with literature on corresponding data, demonstrating the validity of the modeling approaches used. Results indicate considerable hindrance to diffusion in porous media relative to bulk oil and relates to the tortuosity and constrictivity of the rock matrix. The diffusion coefficient of methane in bulk oil is 3.8 × 10−9 m2/s. In our limestone sample, this diffusion coefficient drops by one order of magnitude, ranging between 1.5 to 6.5 × 10−10 m2/s and, it drops by another order of magnitude in the Bakken shale sample to 2.0 × 10−11 m2/s.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84753266","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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