Journal of Petroleum Technology最新文献

{"title":"Seismic Reprocessing Overcomes Uncertainty in Offshore Egyptian Field","authors":"C. Carpenter","doi":"10.2118/0224-0089-jpt","DOIUrl":"https://doi.org/10.2118/0224-0089-jpt","url":null,"abstract":"\u0000 \u0000 This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 214066, “Seismic Reprocessing Leads to New Breakthroughs—A Successful Case in the ASH Field, AG Basin in Egypt,” by Mohamed Elokr and Ahmed Lotfy, Kuwait Energy Egypt, and Wei Xing, United Energy Group, et al. The paper has not been peer reviewed.\u0000 \u0000 \u0000 \u0000 The ASH oil field is in the eastern portion of the AG Basin in Egypt. The Lower Cretaceous Alam El Bueib is the main oil-producing formation. Because of the high heterogeneity of the Abu Roash succession, in addition to the influence of thick limestone of the Upper Cretaceous and the influence of multiple complex faults, the quality of seismic data is very poor, requiring seismic reprocessing. Two key techniques were used to achieve the goal: New vertical seismic profile (VSP) well data were acquired to adjust the velocity model, and common reflection angle migration (CRAM) prestack depth migration (PSDM) was used for reprocessing.\u0000 \u0000 \u0000 \u0000 The ASH field produces oil from the Aptian Lower Cretaceous reservoir. The ASH structure is interpreted as an elongated east-northeast/west-southwest anticline with intensive breaching on the downthrown side of northwest/southeast to west-northwest/east-southeast-oriented normal faults with obvious signature of synsedimentary activities. The entire area was subject to a series of tectonic events affecting the Western Desert, which led to a complex fault regime clearly recognized in the ASH structure by a series of horizontal displacement across the northwest/southeast faults. Strike/slip to oblique-slip faults also are observed from thicknesses of the cretaceous formations, creating significant difficulty in fault definition. The 3D seismic data acquired in 2007 suffered from losing amplitude of the Lower Cretaceous and deep Jurassic reflectors because of the complex structure. The strong carbonate markers disappear north of the field, where high, dense fault intersection is present closing from the main bounding fault. Loss of seismic amplitude could have severe effects on of the future economics of the field.\u0000 The seismic survey was reprocessed two times without significant enhancement of the fault imaging. PSDM was run without velocity control, resulting in an uncertain velocity model with inaccurate fault imaging and a mismatching between actual and prognosed depths of the drilled wells of greater than 50 m. This contradiction in reservoir mapping meant that the northern portion of the field remained unexplored.\u0000 Acquiring VSP in the recently drilled well encouraged reprocessing of the 3D seismic survey using well velocity as a control point in adjusting the seismic velocity model, and application of CRAM technology to improve fault imaging and appraise the uncertain area of the ASH field.\u0000 \u0000 \u0000 \u0000 CRAM was developed as a type of beam migration. Asymptotic ray tracing is performed, assuming that one-way diffraction rays from the subsurface image point to the su","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"118 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139684713","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":"Machine Learning Provides Fracture Analysis, Mapping for CCUS","authors":"C. Carpenter","doi":"10.2118/0224-0092-jpt","DOIUrl":"https://doi.org/10.2118/0224-0092-jpt","url":null,"abstract":"\u0000 \u0000 This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 214996, “Machine-Learning Application for CCUS Carbon Storage: Fracture Analysis and Mapping in the Illinois Basin,” by Guoxiang Liu, SPE, US Department of Energy, and Abhash Kumar and William Harbert, SPE, Contractors, et al. The paper has not been peer reviewed.\u0000 \u0000 \u0000 \u0000 The monitoring of storage reservoirs to ensure safe, long-term storage of CO2 and to derisk operations and storage management is undergoing dynamic shifts, expanding opportunities for implementing innovative techniques and applications, especially for commercial-scale deployment. In the complete paper, a method with multitiered analysis has been developed to leverage advanced machine-learning (ML) techniques to process passive seismic monitoring data acquired during an injection period along with pumping/injection pressure and rate in the Illinois Basin for potential fracture and fault analysis.\u0000 \u0000 \u0000 \u0000 This study is part of the Science-Informed ML for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative funded by the US Department of Energy Carbon Storage Program. The outcomes of the SMART Initiative are science-informed, ML-based tools that can be applied at carbon storage sites throughout the nation and the world to achieve the following objectives:\u0000 - Improve the ability to consolidate technical knowledge, site-specific characterization information, and real-time data in a digestible way\u0000 - Enable the optimization of carbon-storage reservoirs by creating a capability for real-time forecasting of the behavior of such reservoirs\u0000 - Improve the ability to understand and communicate subsurface behavior during carbon-storage operations to nonexperts\u0000 \u0000 \u0000 \u0000 In the authors’ study, a multitiered, data-driven approach was created by integrating all available measurement data to visualize fracture networks. The data sets included measurements from drilling, log and core testing, injection and downhole pressure measurements, and five vertical-pressure-monitoring gauges, providing a wealth of detail on the fracture networks. A fracture network encompasses natural fractures, induced or hydraulic fractures, and the dynamic response of such fractures, culminating in a comprehensive understanding of this system.\u0000 Because of the wide range of resolutions and scales of the data sets, the fracture network was mapped into 19 distinct time windows over a 3-year injection period by analyzing pumping data, which included CO2 injection and bottomhole pressure. Passive seismic data (microseismic) were compartmentalized into these time windows, similar to the industry practice of compartmentalizing microseismic data into separate stages for high-pressure fluid- injection activities (i.e., induced fracturing). In each of these time windows, the b-value of the associated microseismic population was estimated. Furthermore, event-occurrence time and distance from the treatment well","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"36 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139815649","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":"Big Players Pivot in Response to Regulatory Pressures","authors":"P. Boschee","doi":"10.2118/0224-0010-jpt","DOIUrl":"https://doi.org/10.2118/0224-0010-jpt","url":null,"abstract":"\u0000 \u0000 Early January brought with it significant changes in the environmental side of the oil and gas industry. ExxonMobil and Chevron, the two largest US oil producers, announced they will exit California, and the Biden administration froze LNG export approvals.\u0000 After 50 years of producing oil in California, ExxonMobil will take a $2.5 billion writedown of the value of some of its California properties to be recorded in its fourth-quarter earnings. The company said the decision is primarily related to its Santa Ynez operations off the coast of Santa Barbara.\u0000 Its US Securities and Exchange Commission (SEC) filing said, “While the Corporation is progressing efforts to enable a restart of production, continuing challenges in the state regulatory environment have impeded progress in restoring operations.”\u0000 After the Refugio oil spill in May 2015 (approximately 100,000 gal), resulting from a leak from a pipeline owned by Plains All American Pipeline, ExxonMobil acquired the damaged asset in October 2015. Just a few months before the purchase, the Santa Barbara County Board denied ExxonMobil’s request to truck its oil produced off the coast of Gaviota to its Las Flores Canyon processing facility and on to refiners located in Pentland, California.\u0000 Seeking an alternative, ExxonMobil planned to replace two stretches of the 112-mile corroded pipeline for transit of its oil.\u0000 Met with opposition to replace the damaged pipeline and denied permission to repair and restart production at the site (halted since 2015), ExxonMobil is now selling the Santa Ynez operation to Sable Offshore, a blank-check company created in 2020. The company will loan Sable the money for the purchase of its three offshore production platforms, pipeline, and onshore processing facility.\u0000 Sable’s agreement with ExxonMobil requires production to be started by early 2026 or the assets and liabilities revert to ExxonMobil.\u0000 Chevron, headquartered in San Ramon, California, will write down $3.5 billion to $4 billion in assets, citing its home state’s regulations that “have resulted in lower anticipated future investment levels.” The company intends to continue operating its oil fields and related assets.\u0000 In the SEC filing, Chevron wrote it also will incur fourth-quarter charges related to decommissioning of US Gulf of Mexico assets that have reached the end of their productive lives. The company sold some of those assets, but US law stipulates that previous owners may be responsible for those costs if the current owner declares bankruptcy. Chevron wrote it’s “probable” that it may see such costs.\u0000 January closed with another unexpected announcement on 26 January. The Biden administration paused decisions on permits to export LNG to non-free trade agreement countries to review current projects seeking approvals.\u0000 US Energy Secretary Jennifer Granholm stated, “We must review export applications using the most comprehensive, up-to-date analysis of the economic, environmental, and national se","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139832815","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":"Fiber-Optic Strain Measurements Aid Fracture Characterization","authors":"C. Carpenter","doi":"10.2118/0224-0081-jpt","DOIUrl":"https://doi.org/10.2118/0224-0081-jpt","url":null,"abstract":"\u0000 \u0000 This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 3864861, “Geomechanics Modeling of Strain-Based Pressure Estimates: Insights From Distributed Fiber-Optic Strain Measurements,” by Wei Ma and Kan Wu, Texas A&M University, and Ge Jin, Colorado School of Mines. The paper has not been peer reviewed.\u0000 \u0000 \u0000 \u0000 The combination of Rayleigh frequency shift distributed strain sensing (RFS-DSS) and pressure-gauge measurements has been reported recently in field applications. The main objective of the study detailed in the complete paper is to investigate the relationship between strain change and pressure change under various fractured reservoir conditions and provide guidelines for better using this novel strain/pressure relationship to estimate conductive fractures and pressure profiles.\u0000 \u0000 \u0000 \u0000 With a spatial resolution of 20 cm and a sensitivity of less than 1 με, RFS-DSS can measure mechanical strain changes along the fiber with higher accuracy and sensitivity than low-frequency distributed acoustic sensing measurements. The field applications of RFS-DSS have improved the understanding of near-well and far-field fracture characteristics and the relationship between stimulation and production in unconventional reservoirs.\u0000 Although some numerical modeling works have been conducted to study the mechanisms of RFS-DSS data sets, the sensitivity, or influencing factors, of the relationship between strain change and pressure change along the fiber are still unclear.\u0000 In this work, the authors use a coupled geomechanics and fluid-flow simulator to simulate the strain change and pressure change measured along the producing and monitoring wells during both stable production and shut-in periods.\u0000 \u0000 \u0000 \u0000 A 3D multilayer reservoir model with dimensions of 300×400×55.82 m was created using Permian Basin data sets. The reservoir was discretized into 553×129×5 gridblocks. To ensure accurate simulation of field RFS-DSS measurements, the mesh was refined around the fracture and wellbore. The fracture width was set to be the same as the RFS-DSS spatial resolution (0.2 m), and the grid size was set to 5 m except for the refined region. As shown in Fig. 1, the reservoir had 11 perforation clusters along the producing well and the monitoring well was 65 m away from the producing well. A fiber cable was installed on both wells to measure the RFS-DSS data set. The producing well was operated for 240 days before being shut in for 4 days, followed by a 1-day reopening and then continued production for 1 year. The pressure decline was 30–40 psi during the 1-day stable production period. Note that the moment after producing 239 days was taken as the reference time to calculate the strain change during the 1-day production (239–240 days) and the moment after 240 days as the reference time to calculate the strain change during the shut-in period (240–244 days).\u0000","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"33 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139684617","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":"Chevron Applies Some Unconventional Thinking To Try To Make Shale EOR a Standard Treatment","authors":"Stephen Rassenfoss","doi":"10.2118/0224-0024-jpt","DOIUrl":"https://doi.org/10.2118/0224-0024-jpt","url":null,"abstract":"In the shale business, the closest thing now to enhanced oil recovery (EOR) is improved techniques.\u0000 During an earnings call last November an analyst asked EOG Resources executives about their enhanced completion technique which EOG reported was adding 20% to first-year well production in the Permian.\u0000 Improved completions have allowed operators to significantly increase early production year after year, but after that, steep declines are a given.\u0000 Back in 2016, EOG was talking about how it was increasing oil production significantly by injecting millions of cubic feet of gas a day into wells in the Eagle Ford. It triggered an EOR field-testing boom by competitors hoping to match reported reserve increases of “30 to 70%.”\u0000 In a 2017 JPT story, Deepak Devegowda, a petroleum engineering professor at the University of Oklahoma, said, “This is the name of the game. Everybody is talking about EOR and pumping money into trials of EOR.”\u0000 Now the only mention of the acronym EOR on EOG’s website is an item in its corporate history timeline for 2016: “We commercialized the first enhanced oil recovery process, or EOR, in shale.”\u0000 In recent years, reported shale EOR work has been mostly in the form of occasional papers describing production uplift by companies selling ways to increase production by injecting gas or chemicals.\u0000 EOR effectiveness isn’t the issue, according to Todd Hoffman, a petroleum engineering professor at Montana Tech University who wrote two papers evaluating EOG’s methods cited in two Chevron papers.\u0000 “The EOG field work showed us that these projects can produce significant additional oil and be economically positive,” he said. The problem is that drilling and fracturing wells delivers “higher economic returns than the EOG-style EOR projects with the huge compressors, high gas rates, and high injection pressures.”\u0000 Last year in the middle of this EOR drought, Chevron did something different. It delivered two papers revealing a major company-scale effort to find ways to use chemical and gas injections to economically produce more oil.\u0000 The papers presented at the 2023 Unconventional Resources Technology Conference (URTeC) reported on field tests of surfactants and natural gas injection on Permian Basin wells which delivered sufficiently encouraging results to justify an expanded testing program. (URTeC 3870505 and URTeC 3871386).\u0000 Chevron described a systematic effort by its corporate technical unit and its Mid-Continent business unit to rethink shale EOR methods based on the unconventional nature of flow through fractured reservoirs and the economic realities in a business where new EOR technology is competing with the profitable status quo.\u0000 Its methods challenge accepted notions about the role of EOR. In SPE’s disciplines, EOR normally falls under the production topic, “marginal aging fields.” What Chevron tested is better described by the topic, “well interventions.”\u0000 Rather than looking at these techniques as a way to eke out the las","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"56 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139874053","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":"AI-Based System Automates Textual Classification of Daily Drilling Reports","authors":"C. Carpenter","doi":"10.2118/0224-0055-jpt","DOIUrl":"https://doi.org/10.2118/0224-0055-jpt","url":null,"abstract":"\u0000 \u0000 This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 32978, “Development and Implementation of an AI-Based System To Automate Textual Classification on Daily Drilling Reports,” by Stephan Perrout, Aliel F. Riente, and Guilherme S.F. Vanni, SPE, Petrobras, et al. The paper has not been peer reviewed. Copyright 2023 Offshore Technology Conference. Reproduced by permission.\u0000 \u0000 \u0000 \u0000 Structured daily drilling reports (DDRs) are a rich source of information that allows better planning, more-accurate risk analysis, and improved key performance indicators and contracts. However, such information is originally stored in a free-text and unstructured format, which becomes difficult for efficient data mining. With the advance of artificial intelligence (AI) technologies, particularly AI language models, applying such techniques over unstructured data has become critical to digital transformation. The complete paper presents an approach for automatic DDR classification that incorporates new techniques of AI.\u0000 \u0000 \u0000 \u0000 This work addresses the complex task of automatic classification of DDRs according to a newly proposed ontology. The ontology follows a hierarchical model that classifies actions into three or four levels depending on the intervention, considering drilling, completion, and abandonment. Each event has an ontology built and reviewed by experts in oil and gas.\u0000 Classifying DDR constitutes a demanding task, and effectively exploiting AI-based models represents a promising solution. This work bridges the gap by proposing a classifier based on transformers along with recurrent neural networks (RNNs) to classify reported events described in unstructured text related to drilling, completion, and abandonment interventions. A large number of DDRs was used for training and validation of the proposed classifier, yielding promising results for key processes in the company.\u0000 \u0000 \u0000 \u0000 Bidirectional Long Short-Term Memory. Early neural-network models are characterized by inputs of fixed length. This is a drawback when working with texts, however, because sentences vary in their number of words. To overcome such an issue and to process data sequentially, RNNs were proposed. The RNNs are characterized by a set of parameters inherent from the early models plus an internal memory (a hidden or internal state) responsible for storing the context of the sequence being processed.\u0000 Long short-term memory (LSTM) is a variation of RNN proposed to mitigate two problems: Information can be easily lost when processing very long sequences, and the gradient can become quite low because of the high number of mathematical operations performed during the processing while remaining far from reaching the threshold. LSTM consists of a set of parameters called the input gate, forget gate, and output gate that control information flow through the network. This set of additional parameters helps to maintain only what is important for the interna","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"40 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139686294","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":"Rig Automation Empowers Well Construction in Ecuador","authors":"C. Carpenter","doi":"10.2118/0224-0052-jpt","DOIUrl":"https://doi.org/10.2118/0224-0052-jpt","url":null,"abstract":"\u0000 \u0000 This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 216249, “Digital Innovation of Well-Construction Process in Ecuador Through Rig Automation,” by Karen Peña, Kevin Etcheverry, and Hugo Quevedo, SPE, SLB, et al. The paper has not been peer reviewed.\u0000 \u0000 \u0000 \u0000 Artificial intelligence (AI)-based digital drilling technology was implemented in two mature fields in Ecuador that represent 33% of the country’s oil production. The drilling campaign’s main strategy included the deployment of a novel automation solution on two rigs, resulting in the optimization of the well-construction process. In the complete paper, the authors present the results of implementation of a rig-automation solution applied to 20 wells in 2022.\u0000 \u0000 \u0000 \u0000 The authors detail the validation, optimization, and implementation of a drilling software to automate work flows and the installation and commissioning of associated hardware components. The following key indicators and objectives were established:\u0000 - Validation of drilling-software work flows\u0000 - Achievement of a 75% average in automation control\u0000 - Improvement of rate of penetration (ROP) by 5%\u0000 - Reduction of pre- and post-connection times by at least 30%\u0000 - Real-time tuning of parameters\u0000 - Training of all personnel involved in the use of the drilling-software package\u0000 - Installation and commission of hardware components\u0000 \u0000 \u0000 \u0000 The digital solution is an advanced software system that brings automation capabilities to drilling rigs, analogous to the different levels of automation found in automobiles. By drawing a parallel to car automation, one can better understand the system’s functionality and benefits.\u0000 Level 1 consists of task automation, comparable to automatic driving features such as cruise control. In this context, the drilling software takes on the role of automating specific tasks within the drilling process.\u0000 Level 2 involves process automation, similar to a car’s ability to autonomously park itself. The digital solution automates selected processes in drilling operations that enable efficient and precise execution.\u0000 Level 3 encompasses adaptive automation, akin to a self-driving car that dynamically adapts to its surroundings. The drilling software continuously analyzes the real-time conditions of the wellbore and suggests optimal drilling parameters based on proprietary algorithms that leverage the well-known DeTournay model principle.\u0000 The drilling software actively controls four key rig machines: the drawworks, topdrive, automated driller, and mud pumps. The solution adjusts drilling parameters intelligently, optimizing the drilling process and improving overall efficiency and drilling stability.\u0000","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"35 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139811623","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":"Approach to Perforation Interval Selection Uses AI-Assisted Image Interpretation","authors":"C. Carpenter","doi":"10.2118/0224-0078-jpt","DOIUrl":"https://doi.org/10.2118/0224-0078-jpt","url":null,"abstract":"\u0000 \u0000 This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 216856, “ML-Driven Integrated Approach for Perforation Interval Selection Based on Advanced Borehole-Image AI-Assisted Interpretation,” by Alexander Petrov, SPE, Mounir Belouahchia, SPE, and Abdelwahab Noufal, SPE, ADNOC. The paper has not been peer reviewed.\u0000 \u0000 \u0000 \u0000 In the complete paper, the authors propose an artificial-intelligence (AI)-assisted work flow that uses machine-learning (ML) techniques to identify sweet spots in carbonate reservoirs. This process involves annotation of geologic features using a well database, with supervision from subject-matter experts (SMEs). The resulting ML model is tested on new wells and can identify pay zones, perforation intervals, and stress analysis. The models successfully detect fractures, breakouts, bedding planes, vugs, and slippage passages with pixel-level precision, reducing borehole-image (BHI) analysis time.\u0000 \u0000 \u0000 \u0000 The use of BHIs requires manual interpretation and data identification, heavily relying on the expertise and time of SMEs. A widely adopted approach to address this challenge is the use of supervised computer-vision algorithms, a subfield of AI. These algorithms optimize the task function or model based on examples they have learned from data during training. However, when applied to BHIs, certain ML challenges must be addressed, including the following:\u0000 - Detecting features in wells from different reservoirs using a model trained on wells from one reservoir can be highly challenging because reservoirs may exhibit distinct geological characteristics.\u0000 - The handling of parts of BHIs with missing data, depicted by vertically slanted white strips, poses considerable difficulty. Therefore, the authors created a deep-learning approach based on a generative adversarial network architecture to fill the gaps automatically (Fig. 1).\u0000 - The labels provided by geologists often do not have pixelwise precision, causing the machine to become confused while trying to learn inconsistent patterns.\u0000 The authors use a convolutional neural network (CNN) to compute a probability map for pixels belonging to specific classes. In this application, a class is defined as any of the heterogeneities in the BHI; however, this method is applicable to any type of heterogeneities in an image. After training, the CNN module provides the optimal probability for each pixel in the image.\u0000 To classify regions in the BHI based on heterogeneities, a class-specific threshold is established. Pixels with values above the thresholds are assigned to the corresponding class, while those below the thresholds are assigned to the background.\u0000 \u0000 \u0000 \u0000 A new approach for borehole-derived porosity was developed in-house to overcome the limitations of existing techniques widely used in the industry. This approach capitalizes on BHIs for multiple analyses, including structural dip assessment, fault and fracture identification, and determi","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"32 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139830094","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":"BKV CEO: If You Have the Skills To Pay the Bills, CCS Is a ‘Tremendous Business’","authors":"Trent Jacobs","doi":"10.2118/0224-0018-jpt","DOIUrl":"https://doi.org/10.2118/0224-0018-jpt","url":null,"abstract":"Shale gas producer BKV Corp. has made the leap into the US carbon capture and storage (CCS) sector, becoming the latest upstream firm to challenge the idea that only industry giants can make significant moves in this emerging arena.\u0000 Founded in 2015 as a privately held subsidiary of Thailand’s coal and energy conglomerate Banpu, BKV and its fewer than 400 employees have quickly built the company into the 17th largest gas producer in the US. In addition to its upstream operations in the Barnett and Marcellus shales, BKV’s business model borrows from its Thai energy roots and includes ownership of two natural gas power plants in Texas.\u0000 But the firm is better known within upstream technical circles for its leadership in refracturing horizontal wells in the Barnett where it is the largest operator both in terms of acreage and flowing wells.\u0000 No stranger to diversification, BKV is now shifting its focus to CCS—a market anticipated to balloon almost fivefold from $3 billion to over $14 billion by the end of the decade. This growth is being propelled in the US by new legislation offering $85 in tax credits for each ton of CO2 sequestered, effectively turning the greenhouse gas into a valuable commodity.\u0000 The company’s inaugural CCS project, in collaboration with Dallas-based EnLink Midstream, launched this past November in Bridgeport, Texas. Called the Barnett Zero Project, BKV and its partner are targeting the sequestration of approximately 210,000 mtpa of CO2e. Hitting that target means potentially generating over $17.8 million in annual tax credits, a sum that offers a swift return on investment for those who can manage costs.\u0000 BKV has also established a new business unit called dCarbon Ventures which is leading a separate CCS joint venture in the Barnett play called Cotton Cove. The $17.6-million project, $9 million of which will be put up by BKV, is expected to begin injecting up to 45,000 mtpa by the end of next year. Beyond that, BKV and its subsidiaries have secured rights for a large-scale project spanning 21,000 acres in neighboring Louisiana which would source its emissions from the industrial and petrochemical plants around the New Orleans area.\u0000 Steering these ambitious projects is BKV’s CEO, Chris Kalnin, alongside Lauren Read, vice president of the gas company’s dCarbon Ventures. Under their leadership, BKV hopes to achieve net-zero Scope 1 and 2 emissions by next year—decades ahead of most industry reduction targets. The company is not stopping there and is ambitioning to do what most US-based operators have so far refrained from, which is to offset its Scope 3 emissions sometime next decade.\u0000 In the following Q&A, Kalnin and Read discuss the motivations behind the Barnett Zero Project, its significance in the context of independent producers, and what it signals about BKV’s broader strategy.","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139890082","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":"Big Players Pivot in Response to Regulatory Pressures","authors":"P. Boschee","doi":"10.2118/0224-0010-jpt","DOIUrl":"https://doi.org/10.2118/0224-0010-jpt","url":null,"abstract":"\u0000 \u0000 Early January brought with it significant changes in the environmental side of the oil and gas industry. ExxonMobil and Chevron, the two largest US oil producers, announced they will exit California, and the Biden administration froze LNG export approvals.\u0000 After 50 years of producing oil in California, ExxonMobil will take a $2.5 billion writedown of the value of some of its California properties to be recorded in its fourth-quarter earnings. The company said the decision is primarily related to its Santa Ynez operations off the coast of Santa Barbara.\u0000 Its US Securities and Exchange Commission (SEC) filing said, “While the Corporation is progressing efforts to enable a restart of production, continuing challenges in the state regulatory environment have impeded progress in restoring operations.”\u0000 After the Refugio oil spill in May 2015 (approximately 100,000 gal), resulting from a leak from a pipeline owned by Plains All American Pipeline, ExxonMobil acquired the damaged asset in October 2015. Just a few months before the purchase, the Santa Barbara County Board denied ExxonMobil’s request to truck its oil produced off the coast of Gaviota to its Las Flores Canyon processing facility and on to refiners located in Pentland, California.\u0000 Seeking an alternative, ExxonMobil planned to replace two stretches of the 112-mile corroded pipeline for transit of its oil.\u0000 Met with opposition to replace the damaged pipeline and denied permission to repair and restart production at the site (halted since 2015), ExxonMobil is now selling the Santa Ynez operation to Sable Offshore, a blank-check company created in 2020. The company will loan Sable the money for the purchase of its three offshore production platforms, pipeline, and onshore processing facility.\u0000 Sable’s agreement with ExxonMobil requires production to be started by early 2026 or the assets and liabilities revert to ExxonMobil.\u0000 Chevron, headquartered in San Ramon, California, will write down $3.5 billion to $4 billion in assets, citing its home state’s regulations that “have resulted in lower anticipated future investment levels.” The company intends to continue operating its oil fields and related assets.\u0000 In the SEC filing, Chevron wrote it also will incur fourth-quarter charges related to decommissioning of US Gulf of Mexico assets that have reached the end of their productive lives. The company sold some of those assets, but US law stipulates that previous owners may be responsible for those costs if the current owner declares bankruptcy. Chevron wrote it’s “probable” that it may see such costs.\u0000 January closed with another unexpected announcement on 26 January. The Biden administration paused decisions on permits to export LNG to non-free trade agreement countries to review current projects seeking approvals.\u0000 US Energy Secretary Jennifer Granholm stated, “We must review export applications using the most comprehensive, up-to-date analysis of the economic, environmental, and national se","PeriodicalId":16720,"journal":{"name":"Journal of Petroleum Technology","volume":"31 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139892696","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}