Day 2 Mon, February 20, 2023最新文献

{"title":"A Dynamic Residual Learning Approach to Improve Physics-Constrained Neural Network Predictions in Unconventional Reservoirs","authors":"Syamil Mohd Razak, J. Cornelio, Young Cho, Hui-Hai Liu, R. Vaidya, B. Jafarpour","doi":"10.2118/213289-ms","DOIUrl":"https://doi.org/10.2118/213289-ms","url":null,"abstract":"\u0000 Predictive models that incorporate physical information or constraints are used for production prediction in subsurface systems. They come in many flavors; some include additional terms in the objective function, some directly embed physical functions and some use neural network layers to explicitly perform physical computations. In unconventional reservoirs that are characterized by tight fractured formations, a detailed and reliable description of the flow and transport processes is not yet available. Existing physics-based models use overly simplifying assumptions that may result in gross approximations. In physics-constrained neural network models, the network predictive performance can be degraded when the embedded physics does not represent the relationship within the observed data.\u0000 We propose dynamic residual learning to improve the predictions from a physics-constrained neural network, whereby an auxiliary neural network component is introduced to compensate for the imperfect description of the constraining physics. When a dataset cannot be fully represented by a trained physics-constrained model, the predictions come with a large error or residual when compared to the ground truth. A deep neural network utilizing a masked loss function to enable learning from wells with varying production lengths is employed to learn the complex spatial and temporal correspondence between the well properties such as formation and completion parameters to the expected residuals. The new formulation allows for dynamic residual correction, avoids unintended bias due to less-than-ideal input data, and provides robust long-term predictions when partially-observed timesteps are present. The proposed method results in a final prediction that combines the prediction from the physics-constrained neural network with the predicted residual from the auxiliary neural network component. Several synthetic datasets with increasing complexity as well as a field dataset from Bakken are used for demonstration.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131958739","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}

{"title":"Advancements in Remedial Sand Control Solutions - Successful Deployment in Three Well Campaign","authors":"E. McKay, Nicola Wigg, K. Parrott, Baida Iqlima","doi":"10.2118/213642-ms","DOIUrl":"https://doi.org/10.2118/213642-ms","url":null,"abstract":"\u0000 Regaining sand control integrity in existing completions has been become an increasing challenge to overcome in recent years. Sand control challenges can occur over the life of the well, in the initial completion design, failure of existing downhole equipment or due to increased water production in later life. All of which need to be addressed using a technology which does not succumb to the same fate as any existing technology. Conventional remedial sand control methods vary in complexity, cost, risk, longevity and have associated weaknesses often resulting in reduced production. A novel thru tubing remedial sand control solution has recently been deployed for an operator in Indonesia which can be run on coil tubing or slickline. It is designed to transit tight restrictions within the upper completion and still set and conform to larger casing/screen IDs where control of sand has been lost. The key to the technology is the use of a unique conformable open cell matrix polymer (OCMP) as the sand retention layer which enables the tool to be fully compressed during deployment but will enlarge when at depth, filling the annular gap. The OCMP creates a tortuous flow path and the polymeric nature of the filter removes the energy out of any sand grain impingement reducing erosional effects. We present a review of three recent well interventions in both oil and gas wells that utilized this technology.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134633954","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}

{"title":"Production Forecasting in Tight Gas Reservoirs Using Long Short-Term Memory Methods (LSTM)","authors":"Afrah Qoqandi, Omar Alfaleh, M. Ramadan, Uchenna Odi","doi":"10.2118/213343-ms","DOIUrl":"https://doi.org/10.2118/213343-ms","url":null,"abstract":"\u0000 Forecasting the estimated ultimate recovery (EUR) for extremely tight gas sites with long-term transient behaviors is not an easy task. Because older, more established methods used to predict wells with these characteristics have shown important limitations, researchers have relied on new techniques, like long short-term memory (LSTM) deep learning methods. This study assesses the performance of LSTM estimations, compared to that of a physics-based reservoir simulation process.\u0000 With the goal of obtaining reliable EUR forecasts, unconventional tight gas reservoir data is generated via simulation and analyzed with LSTM deep learning techniques, tailored for sequential data. Simultaneously, a reservoir simulation model that is based on the same data is generated for comparison purposes. The LSTM forecasting model has the added benefit of considering operational interventions in the well, so that the machine learning (ML) framework is not disrupted by interferences that do not reflect the actual physics of the production mechanism on well behavior.\u0000 The comparison of the data-driven LSTM deep learning model and the physics-based reservoir simulation model estimations was performed using the latter framework as a benchmark. Findings show that the AI-assisted LSTM model provides predictions similarly accurate to the ones estimated by the physics-based reservoir model, but with the added capability for long-term forecasting. These data-driven EUR models show great promise when analyzing unusually tight gas reservoirs that feature time series well information, which can improve estimations about recovery and point engineers towards better decisions regarding the future of reservoirs. Therefore, exploring deep learning methods featuring varying types of artificial neural networks in greater detail has the potential to significantly benefit the oil and gas sector.\u0000 When compared to other machine learning methods, novel deep learning techniques have advantages that remain underexplored in the literature. This paper helps fill this gap by providing a valuable comparison between older prediction methods and new estimation simulations based on neural networks that can predict long-term behaviors.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133678806","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}

{"title":"Successful Introduction of a Novel, High Dogleg Rotary Steerable System","authors":"George Sutherland, Jeffrey Lasater, Gary D. Althoff, J. Verma","doi":"10.2118/213687-ms","DOIUrl":"https://doi.org/10.2118/213687-ms","url":null,"abstract":"\u0000 Rotary Steerable Systems (RSS's) have proven beneficial over conventional steerable motor systems, which has driven significant market uptake over the last several decades. Consequently, applications for RSS's have expanded and encouraged RSS technology developers to meet these ever-changing market demands. Modifications to the basic proven RSS methods, attempted independent reproductions of those methods, and other novel methods have emerged to fulfill these market demands.\u0000 The initial RSS method and technique were invented and proven in the late 1990s, and common ways of creating wellbore deflection emerged, allowing the industry to attempt the classification of these methods. These classifications were an attempt to gain a better understanding of the advantages and disadvantages of each and help understand where and what version of technology to apply for an ever-increasing expansion of applications.\u0000 This paper describes the attempts at classification of RSS's, then addresses the drivers, development, and field trial results of a new method for placing wells using a high dogleg automated rotary steering system (SwR; Steering-while-Rotating).\u0000 The SwR was targeted to meet market changes identified in 2016 and projected out ten (10) years by the SwR technical team. Simplicity, fostering reliability and value were major design tenets. A high dogleg curve (20°/100’) design, enabling \"one-run, Vertical, Curve, and Lateral\" bottom hole assemblies, two-way (uplink-downlink) downhole communications along with autonomous self-steering capability, also drove the SwR development.\u0000 The initial SwR prototype system for 8-3/8\"-9-7/8\" hole sizes was built, and field trials began in Q3 of 2019. The SwR team weathered the global Covid-19 pandemic of 2020-21 with the rest of the world and deployed systems to the Middle East, while also securing and executing trial and commercial runs within North America in 2021 and 2022. Conclusions are based upon, and data is presented from thirty-seven (37) bit runs and the first 50,000 feet drilled with the SwR.\u0000 The SwR team has delivered a unique steering method to the industry and presents the early run data demonstrating the SwR technology capability to drill challenging well profiles, in challenging environments. The SwR technology was designed for the RSS market of today and for several years to come improving the value proposition for modern RSS well placement technology.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116122141","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}

{"title":"Modeling CO2 Geologic Storage Using Machine Learning","authors":"A. Alali","doi":"10.2118/213565-ms","DOIUrl":"https://doi.org/10.2118/213565-ms","url":null,"abstract":"\u0000 Over the upcoming years, storing CO2 into geological formations would contribute significantly to the international efforts to address climate challenges due to greenhouse gas emissions. Carbon Capture and Storage (CCS) projects require immense capital investments to complete multiple phases, namely careful site selection, planning, design, and execution. Modeling of surface and subsurface CO2 flow plays a major role not only in design optimization but also in site screening and capacity estimation. This study focuses on modeling multiphase flow of CO2 in underground formations with particular emphasis on the fraction of the CO2 injected that can be trapped. Key interest is given to a trapping mechanism that can keep CO2 stored for long-term in target formations, namely residual trapping. The main objective of this work is to find more efficient ways to proxy model this process with its complex physics.\u0000 There have been multiple recent reservoir simulator numerical enhancements to model CO2 trapping in CCS accurately. However, these complex enhancements have created computational difficulties when attempting to capture unique CO2 fluid physical and chemical subsurface processes such as relative permeability hysteresis. Such numerical challenges make the modeling inefficient and computationally expensive. Therefore, this study introduces more-efficient modeling techniques based on machine learning to make simulations more practical and accessible. By generating a sufficiently large training dataset utilizing a computationally-enhanced numerical simulator with a wide range of input parameters including permeability, porosity, etc., a machine learning model was constructed as an alternative to conventional numerical simulation.\u0000 The effectiveness of the machine-learning models is presented using a test case of a 2D rectangular grid domain of heterogeneous permeability representing a saline aquifer. The goal is to model an injection of CO2 into water under gravity segregation to estimate the fraction of CO2 trapped at the bottom prevented from reaching the top. Even though the training dataset used in this study is relatively small, the machine-learning alternative is able to achieve at least 95% accuracy when tested with new input data in 103 to 104 faster run-times. It is believed that this accuracy can be improved further by increasing the size of the training dataset and exploring other machine-learning models with new hyperparameters. In this study, only a limited number of widely-used techniques is compared, including: Random Forest, K-Nearest Neighbors (KNN), and Multi-Output Regression.\u0000 Accurately modeling the amount of CO2 that can be trapped during CCS applications is vital as this will dictate the available storage capacity for injected CO2; however, this may be a difficult task for most commercial simulators. This study proposes new ways to model such process with enhanced efficiency compared to existing techniques. As most global effo","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127151037","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}

{"title":"A Workflow to Assess the Effect of Lateral Landing, Completion, and Fracturing on Production Potential in an Explorational Clastic Environment","authors":"C. Herrera, AbdulMuqtadir Khan, Abdulrahman A. Almulhim, S. Hamid","doi":"10.2118/213758-ms","DOIUrl":"https://doi.org/10.2118/213758-ms","url":null,"abstract":"\u0000 Three horizontal wells were drilled and completed with hydraulic fracturing in an explorational environment based on reservoir characterization from openhole logs. Limited success in establishing gas production rates showed the need for an integrated technical workflow to be applied for the next well, well-A. After good production results were achieved in well-A, the next phase used three more wells to correlate the production performance based on precise well placement.\u0000 In well-A, openhole sampling was done during drilling of the pilot hole prior to sidetracking the lateral. This was followed by a novel fracturing approach with slickwater hybrid, low-polymer, and CO2 foamed treatments to study the effectiveness of treatments. Post-fracturing diagnostics including a production log and spectral noise log (SNL) were performed to assess production by stage. Three more wells were drilled in the same reservoir, and then a synthetic correlation model was built with resistivity logs to correlate precise lateral landing with the prolific sublayer. Finally, the production performance of all wells was studied based on well placement, fracturing, and the completion approach.\u0000 The first phase of the study of the three wells allowed characterizing well-A in terms of reservoir interval, wellbore orientation, and fracturing strategy. Layer 1 was used to sidetrack the lateral. The post-fracturing production log and SNL indicated the CO2 foamed treatment was the best approach for well-A. The next three wells in the development phase were drilled in layer 1 with good production but inconsistent results. Because the highest flow rate in well-A was seen from the heel part of the lateral, an ultradeep resistivity-correlation bed boundary model was generated from well-A to characterize structural dip, and precise lateral locations were analyzed for all the wells. The model was also used to describe the most prolific sublayer within the layer 1 reservoir. The results showed a strong production dependence on the lateral landing with respect to the defined prolific sublayer. The number of fractures placed also showed a direct relation with gas rates. Finally, a geosteering simulation model was built to be used to further develop the area and detailed recommendations were documented. The ultradeep azimuthal resistivity tool has the capacity to detect ultradeep resistivity up to 100 ft from the borehole. Simultaneously, it can map ultrathin layers, which is necessary for the laminated reservoirs.\u0000 The objectives of precise well placement and rendering productive gas wells in the exploration area through a comprehensive workflow was optimized and analyzed over 4 years. This paper presents systematic findings and a robust framework ready for implementation in future developments.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128875657","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}

{"title":"Understanding the Key Factors Affecting Well Integrity in Horizontal Well Multistage Hydraulic Fracturing","authors":"Waheed Arshad, Khaqan Khan","doi":"10.2118/213677-ms","DOIUrl":"https://doi.org/10.2118/213677-ms","url":null,"abstract":"\u0000 With the significant increase in multistage hydraulic fracturing in the last two decades, occurrence of casing failures has also become noticeable, raising wellbore integrity concerns among operators worldwide. The consequences of casing failures can be varied, but in many cases they affect well production, wellbore accessibility, and, in some rare instances, present well control and associated risks.\u0000 In fact, tubular damage during fracturing is not caused by a single, consistent reason. Rather, it varies greatly across the industry. Investigators have identified several different factors that come into play when identifying tubular fatigue failure when exposed to high stress loads during pressure and temperature cycles in a multistage fracturing operation. Other contributing factors are well trajectory and borehole inclination with respect to the fracture plane, the quality of the cement bond, the development of \"trapped pressures,\" or change in in-situ stresses that could initiate formation movement.\u0000 A parametric study was conducted using worldwide data to evaluate and determine the main factors controlling overall well integrity. Casing failure was defined as a reduction in the internal diameter of the pipe from its initial completion state before hydraulic fracturing. The failure events were studied and compared with the same factors in successful wells.\u0000 This paper provides an insight into the relationship between borehole condition (primarily hole size), well deviation, well azimuth, dogleg severity, pipe centralization, the type of hydraulic fracturing treatment performed (i.e., proppant frac or acid frac) and the risk of pipe deformation. By understanding the primary factors that affect well integrity, the likelihood of casing failure can be predicted and avoided ahead of time, save fracturing costs across high-risk areas, and not jeopardize production from multimillion dollar completions. Managing well integrity is essential for development of oil and gas resources while preserving the environment and assuring safety of personnel.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123317078","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}

{"title":"Understanding Lateral Permeability Variations Using Integrated Logging-While-Drilling Azimuthally Oriented Formation Testing and High-Resolution Imaging in Heterogeneous Carbonate Reservoirs","authors":"Ashok Kumar V, A. Fateh, A. Taher, M. Fouda","doi":"10.2118/213303-ms","DOIUrl":"https://doi.org/10.2118/213303-ms","url":null,"abstract":"\u0000 Permeability is a fundamental petrophysical attribute required to accurately evaluate recoverable reserves and design an appropriate field-development strategy. Because logging tools do not measure absolute permeability, minimizing uncertainty in the evaluation of log-derived permeabilities remains one of the most critical petrophysical challenges in the oil industry. Horizontal development in laterally heterogeneous carbonate reservoirs also requires evaluation of lateral permeability variations to optimize completion design, while maximizing reservoir exposure via precise well placement in real time. This paper demonstrates innovative methods to evaluate lateral permeability variations in heterogenous carbonate reservoirs.\u0000 The workflow for log-derived permeability predictions is based on empirical relationships using nuclear magnetic resonance (NMR), acoustic, and high-resolution imaging tool measurements. These are normalized in an integrated multi-disciplinary approach using core, well test, production logs, and formation-tester mobility data where available. Traditionally, formation-tester tools have been used to obtain single pressure and mobility values at each test station. The logging-while-drilling (LWD) formation tester can be oriented azimuthally to help evaluate permeability anisotropy, which is a key factor for reservoir characterization in laterally heterogeneous reservoir layers. The oriented data can also be used to adjust the well plan in real time to maximize reservoir exposure in the desired \"sweet spot.\"\u0000 Variations in the oriented LWD formation tester measurements at each depth station exhibited favorable correlations to azimuthal changes observed in the LWD high-resolution micro resistivity image. Detailed image analysis further helped to understand the mechanism that governs the azimuthal permeability profile. The combination of oriented LWD formation-tester and high-resolution image data also aided in making better real-time geosteering decisions, as well as in the planning and design of a future field-development program within the local reservoir sector. Operational considerations to maximize data quality rely on an optimized bottomhole assembly (BHA) design, accurate depth control, and robust orientation techniques based on best practices and lessons learned.\u0000 This paper presents an integrated approach for well placement and an improved understanding of flow-unit characterization via first-time use of oriented formation-tester data in conjunction with corresponding high-resolution images in a laterally heterogeneous reservoir.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"75 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123113666","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}

{"title":"Study on Horizontal Well Indirect Fracturing Technology in the Gangue of Broken Soft Coal Seams for CBM Development","authors":"Xuejiao Li, Haifeng Zhao, Chaowei Wang, Dongchenhao Wang, Wenjie Yao, Huaibin Zhen, Zongfei Wang","doi":"10.2118/213751-ms","DOIUrl":"https://doi.org/10.2118/213751-ms","url":null,"abstract":"\u0000 Crushed soft coal seams have the features of low mechanical strength and broken coal structure. Fracturing directly in broken soft coal seams, short and coarse fractures are formed and a large amount of coal powder is produced. In this study, horizontal well indirect fracturing technology in the gangue of crushed soft coal seams was proposed to improve the coalbed methane (CBM) development effect.\u0000 Based on the No. 5 coal seam in the Daning-Jixian block of the Ordos Basin in China, the fracability of the gangue and coal seam were evaluated by logging interpretation, rock mechanical tests and immersion experiments. The technological process of horizontal well staged fracturing in the gangue of crushed soft coal seams was constructed by field test. A corresponding hydraulic fracturing physical simulation experiment was performed, and fracture propagation behaviors were investigated.\u0000 The results show that compared with crushed soft coal seams, gangue has better brittleness and fracability. Horizontal well indirect fracturing in gangue can well stimulate upper and lower coal seams, significantly decrease the fracturing pressure and fracture extension pressure, and reduce the production of coal power. The desirable crack extension and considerably enhanced production effect demonstrated the remarkable engineering feasibility of this technology. The suitable thickness is 0.5~1 m for mudstone gangue, whereas a thickness of 2~3 m is appropriate for interbedded sandstone and mudstone gangue. The stage spacing should be larger than 80 m, and the cluster spacing should be greater than 24 m to avoid the stress shadow effect. Hydraulic fractures initiated from the gangue of coal seams, first spread vertically in the gangue layer and extend rapidly along the interfaces between the coal seams and gangue, then penetrated the lithologic interface and expanded into the coal seams. The upper and lower coal seams were torn open, and 3D complex fractures were formed in the coal seams, creating flow channels for CBM into the horizontal wellbore.\u0000 This research presents a novel technical idea for the CBM extraction of crushed soft coal seams. The findings can offer guidance for the optimal design of horizontal well indirect fracturing in the gangue of crushed soft coal seams.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117312398","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}

{"title":"Identification and Mapping of Gas Reservoir Bitumen","authors":"Ali J Al Solial, Aijaz M. Shaikh, Abdullah K Idrees","doi":"10.2118/213390-ms","DOIUrl":"https://doi.org/10.2118/213390-ms","url":null,"abstract":"\u0000 Reservoirs that have undergone a gas charge after being charge with oil will have oil trapped within the reservoir. The interest of this study is to identify ways to trace that heavy oil, referred to as bitumen, in gas reservoirs from openhole logs along with identifying the controlling parameters on the trapping of this bitumen. The bitumen could be pore-saturating or grain coating.\u0000 This paper looked into the petrophysical logging responses from 3 wells with confirmed bitumen at surface as well as thre other wells with matching signatures, for the purposes of mapping. The main logs considered were Resistivity and density-neutron, with formation testing and elemental spectroscopy being used as additional data sources. Thin sections from the cores, were also used to further identify more controlling parameters that might exist.\u0000 Regardless of the nature of the bitumen's existence within the pore-space it appears that the main controlling parameters are structural. The investigation of petrophysical signatures lead to minor structural changes within the silt being able to provide a trap for the bitumen charge to accumulate. Use of silt-sand-shale analysis allowed to map the presence of the sub-structures under which the bitumen resides further leading to the fact that bitumen presence in the reservoir is structurly controlled. This does explain why bitumen exists in some areas of the reservoirs and not in others. Moreover, this also explains the generally relative low thickness of bitumen. Mapping the layers and ditrubuting them into 3d space will allow for the prediction of where the bitumen occurs as long as a controlling depth, above which bitumen exists, can be identified. Alternatively, flatting the structure to conditions prior to the development of the current seal can be done to better identify where the bitumen could've been trapped.\u0000 Bitumen in deep reservoirs will impact fluid composition and can have impacts on drilling and drilling strategy. Therefore, identifying where the bitumen occurs is of high value to the development of these reservoirs. Further work remains to be done for identification in carbonate reservoirs and potentially further study of more bitumen saturated samples might lead to a better understanding of the phenomenon.","PeriodicalId":249245,"journal":{"name":"Day 2 Mon, February 20, 2023","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115502391","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}