Day 2 Thu, March 14, 2024最新文献

{"title":"Creating a Multiphase Production Model Tailored to Deviated Oil-Producing Wells for Integration as Input into a Machine Learning Model for ESP Survival Analysis","authors":"Wisam Sindi, R. Fruhwirth, Ernst Gamsjäger, Herbert Hofstätter","doi":"10.2118/218123-ms","DOIUrl":"https://doi.org/10.2118/218123-ms","url":null,"abstract":"\u0000 A comprehensive model estimates wellbore production variables, including flow velocities, phase fractions/holdups, fluid properties, pressure/temperature profiles, and Electrical Submersible Pump (ESP) performance metrics. Coupled with instrument data, these inputs support productivity surveillance and ESP status prediction driven by machine learning (ML). The wellbore production model's effectiveness is evaluated by comparing it with industry-sourced field data encompassing muti-probe production logging tool (PLT) measurements from multiphase producing wells.\u0000 This work is based on Nodal Analysis, which involves dividing the wellbore into numerous sections and applying the conservation of mass, momentum, and energy principles to model pressure, temperature, and other essential profiles. Three multiphase flow methods are employed: homogeneous flow, separated flow with slip (Hagedorn-Brown method), and separated flow with slip and flow pattern (Mukherjee-Brill method). Affinity Laws are used to describe the ESP performance. A machine learning model is trained using manually labelled historical data subsets comprising model results and actual field measurements. Its purpose is to recognize ESP operational statuses such as pump off, normal operation, electrical wear, and mechanical wear. Supervised feature selection methods are utilized to identify the most relevant parameters.\u0000 The along the wellbore measurements from PLT e.g. the phase holdup (also referred to as in-situ volume fraction) is in agreement with the modelling results. For a wide range of liquid rates and gas-liquid ratios, flow rates can be determined with an average deviation of less than 10%. Machine learning feature selection methods, such as sequential backward elimination, reveal that production modelling results are crucial for identifying ESP statuses, including mass rate, viscosity, and pump parameters like efficiency. This study demonstrates that hydrodynamic modelling results provide additional information for ML training that electro-mechanical raw data may lack. Thanks to the integration of hydrodynamic modelling and raw data supplied to the ML algorithm, it can classify operational statuses with 99% accuracy and predict ESP failure months in advance.\u0000 When the model is connected to standard wellbore instrumentation, it enables near real-time production monitoring and provides essential hydrodynamic input to ML-based algorithms for continuous monitoring ESP equipment. It can be used as a virtual flowmeter (VFM) or a validation tool for multiphase flowmeters (MPFM), enhancing allocation split accuracy and enabling operators to concentrate on true contributors. The methodology can be integrated into a digital oilfield (DOF) system, employed as a digital twin, or, as demonstrated in this study, integrated into asset modelling with ESP survival analysis and failure prediction using ML.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"27 s77","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140394903","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":"Impact of Impurities on the Economic Assessment of Carbon Dioxide Capture, Transport, and Storage","authors":"Kwang-Yeob Seo, Yoojin Choi, Kun Sang Lee","doi":"10.2118/218087-ms","DOIUrl":"https://doi.org/10.2118/218087-ms","url":null,"abstract":"\u0000 The study proposes a techno-economic evaluation of geological storage of CO2 coupled with enhanced oil recovery based on the composition and price of the CO2 stream. A compositional reservoir model was developed to analyze the effect of CO2 and impurities on oil recovery and storage efficiency. The results indicate that most impurities increase the minimum miscibility pressure between the injected gas and the reservoir fluid. The higher the impurity content of the CO2, the lower the sweep and displacement efficiencies, which decreased oil recovery, while the amount of stored CO2 compared to the injected carbon increased. According to an economic analysis that includes capture, transportation, and storage, the net present values (NPVs) from CO2 composition scenarios ranging from 77.4% to 99.9% are almost identical. However, a sensitivity analysis of the economic parameters indicated that NPV is sensitive to the price of oil, discount rates, and tax policy.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"34 5‐6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140284967","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":"Case Study of Autonomous Inflow Control Devices (AICD) to Control Water Production in Fractured Carbonate Reservoir in Eastern Montana","authors":"Matt McConnell, Rami Jasser, Jake Tappan, S. Fipke","doi":"10.2118/218071-ms","DOIUrl":"https://doi.org/10.2118/218071-ms","url":null,"abstract":"\u0000 Autonomous Inflow Control Devices (AICD) have been commercially available since 2010 and there are many published case studies of wells in sandstone reservoirs, encompassing a wide variety of water and gas control scenarios. There are, however, relatively few documented studies of AICD for water control in fractured carbonate reservoirs. This paper will discuss and compare two trial wells that were completed with AICD in Eastern Montana in late 2022.\u0000 Mission Canyon is a limestone formation of the Mississippian age and is associated with the Williston Basin of the North Central United States. It is composed primarily of oolitic calcarenite consisting of sedimentary carbonate grains. Depending on the grain size, matrix permeability can be relatively low, and a complex network of natural fractures is what dominates fluid flow. These fractures can be good or bad; they can deliver a good oil rate, or they can be direct conduit to the reservoir’s natural bottom-water drive. Consequently, most wells start with 50% water cut and reach 90%+ within a few months. Water volumes can be as high a 3000 barrels of water per day, per well, requiring large-volume pumps and significant water handling & disposal infrastructure. This field trial of AICD technology was designed to reduce water production rates, and then evaluate the impact on additional oil recovery.\u0000 The technology tested was an AICV (autonomous inflow control valve) that utilizes the fluid viscosity and density to autonomously restrict water. The AICV devices were installed in two wells; the first was an existing horizontal producer (retrofit installation) and the second was a newly drilled horizontal well. AICV were installed on 3-1/2\" liners in the open-hole horizontal section, compartmentalized into stages by swellable packers. Each compartment of the well was approximately 150 ft long and was controlled by a dual AICV flow screen. Nodal analysis predicted a 50% reduction in produced water, with an increase of 20-30% oil rate versus the standard open-hole laterals.\u0000 This field study documents the world’s first application of the AICV technology for light oil, water control in a fractured carbonate reservoir. Many valuable lessons were learned on how to best complete and operate the wells. Preliminary results show effective water control, regardless of pressure drawdown. The paper will share production results for each well and attempt to estimate the net effect on oil production and well economics.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"58 S273","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140394686","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":"Overcoming Challenges in Technology Adoption: A Case Study in Fiber Optic Sensing","authors":"M. Hooper, E. Jalilian, J. Hull","doi":"10.2118/218106-ms","DOIUrl":"https://doi.org/10.2118/218106-ms","url":null,"abstract":"\u0000 Adoption of cutting-edge digitization tools in the energy sector is often challenged by an underestimation of value-in-use stemming from a lack of publicly available information regarding the breadth of technological capabilities and associated use-case economics. This paper seeks to address such challenges – as they pertain to advanced fiber optic sensing systems for monitoring of pipelines and other energy infrastructure - by providing readers with a comprehensive overview of the full range of operational applications and current economics for the state-of-the-art in the field, with a focus on case studies and value add benefits that have emerged more recently for many operators.\u0000 Distributed fiber optic sensing (DFOS) continues to see strong commercial growth in the Canadian energy sector, largely due to its exceptional suitability for real time detection of pinhole-level leaks along the full length of long-run pipeline assets. Combining the remarkable sensitivity and lightspeed transmission capabilities of DFOS with the analytical horsepower of the latest machine learning (ML) strategies allows pipeline operators to accurately detect and characterize even minute integrity events (like the pinhole leaks noted above) in real-time, regardless of when or where these occur within their vast asset networks. As a result, many operators have gained at least some familiarity with distributed fiber optic sensing (DFOS) systems and a basic understanding of their performance capabilities and general economics.\u0000 The downside of this singular focus on the leak detection capability and use case is, of course, that industry may elect not to adopt – or at a minimum fail to exploit the full potential of - this rapidly evolving technology, particularly as novel applications dramatically increase DFOS’ value in use. Rapid commercial growth has also driven down DFOS costs as deployment methods and system architectures are optimized over millions of pipeline meters, resulting in an often-substantial gap between perceived adoption cost and real project economics. This combination of capability underestimation and life-cycle cost overestimation presents a major challenge for many technology adoption scenarios, with analysis made all the more difficult by a general lack of publicly available project details.\u0000 This paper reviews case studies from recent DFOS deployments, with a focus on the operational value-in-use realized for a cross-section of commercial applications (i.e., pig tracking, real-time remediation support, temporary pipeline (‘layflat’) management, etc.) as well as the broader business case for life cycle technology costs (i.e., ROI metrics) aimed at providing an accurate understanding of both the costs and capabilities of advanced DFOS systems for integrity management of energy infrastructure. Ultimately the paper will help operators better understand the current state of DFOS technology and make informed decisions regarding its potential and busines","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"85 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140395399","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":"Optimization of Gas Injection Network Using Genetic Algorithm: A Solution for Intermittent Gas Lift Wells","authors":"Ankit Garg, Aman Sharma, S. Rajvanshi, Abhinav Suman, Bhargab Goswami, M. Yadav, Dkj Narayana, Rajesh Tiwary","doi":"10.2118/218028-ms","DOIUrl":"https://doi.org/10.2118/218028-ms","url":null,"abstract":"\u0000 Multiple intermittent gas lift (IGL) wells are typically connected to a centralized high-pressure gas source, which can result in significant fluctuations in gas injection header pressure and subsequent liquid surges in the well fluid header when gas injection is initiated simultaneously in multiple wells. To address the challenge of gas injection interference among intermittent gas lift wells, we propose a mathematical model that utilizes genetic algorithm to optimize the staggering of time cycles, with the goal of achieving minimal interference.\u0000 Genetic algorithms approach provides an effective optimization technique for addressing the time cycle staggering in intermittent gas lift wells. The algorithm involves creating a population of potential solutions, representing each solution as a set of genes or chromosome. In the context of this model, the gas injection time slots for each well are encoded as chromosomes. The developed model utilizes input gas injection time cycles, to compute the best possible time slots for each well. By leveraging the principles of natural selection and evolution, the model iteratively computes the best possible time slots for each well, continuously improving the solutions until convergence is reached. This approach minimizes gas injection interference and enhances the efficiency of gas lift operations.\u0000 The current field practice involves manually staggering the time cycle slots to minimize interference among wells, which becomes impractical with increased well and time slot numbers. Our developed model based on genetic algorithm optimization approach offers an automated and efficient solution for time cycle staggering in intermittent gas lift wells. Despite the NP-hard (non-deterministic polynomial-time hardness) nature of the problem, genetic algorithms provide an effective means of generating near-optimal solutions within a reasonable computational time. By minimizing gas injection interference, this optimization technique enhances the overall efficiency of gas lift operations, preventing production losses. Application of the developed model in the onshore oil field of ONGC demonstrated a significant reduction in gas injection header pressure fluctuations which improved the overall performance of the gas lift system. In this study effect of manually staggered gas injection time cycle, on gas injection network pressure fluctuations is also analysed.\u0000 The population of wells employing intermittent gas lift mode is progressively growing as oil fields undergo browning. This advancement in optimization methodology holds great promise for the oil and gas industry, facilitating the optimization of gas injection time cycle slots leading to reduced pressure fluctuations and improved production efficiency.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"88 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140395544","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":"Critical Elements Extraction from Flowback and Produced Water: From Lab to Field","authors":"A. Ghanizadeh, C. R. Clarkson, A. Bader, B. Tutolo, A. Younis, M. Shabani","doi":"10.2118/218053-ms","DOIUrl":"https://doi.org/10.2118/218053-ms","url":null,"abstract":"\u0000 Flowback and produced water (FPW) from multi-fractured horizontal wells (MFHWs) are possible sources of critical elements (CE) from unconventional hydrocarbon reservoirs. The objective of this study is to compare temporal variations of CE (Li, Mg) concentrations in FPW at lab- and field-scales, with examples from prominent Canadian unconventional hydrocarbon plays. A secondary objective was to evaluate whether CE could be extracted (i.e. ‘leached’) from reservoir rocks by FPW. Quantifying elemental leaching is important for reserves evaluation and identifying the relative importance of mechanisms contributing to CE enrichment in FPW (e.g., fluid mixing vs. fluid-rock interaction).\u0000 High-temperature (150 °C), high-pressure (2200 psi) fluid-rock interaction experiments were conducted on three crushed-rock Montney (siltstones/sandstones) and Duvernay (organic/clay-rich shales) samples with variable composition, fabric, and reservoir quality. Time-lapsed fluid analysis (+30 days), using spectroscopy and ion chromatography (ICP-OES/IC) enabled observations of Li and Mg concentration profiles at the lab-scale. Lab-scale Li and Mg concentration profiles were then compared to post-fracture Li and Mg concentration profiles from multiple MFHWs completed in the Montney and Duvernay formations (public data).\u0000 At the lab-scale, maximum measured Li concentrations for the Montney and Duvernay samples were 0.27 mg/L and 0.53 mg/L, respectively. Maximum lab-scale Li recoveries were significantly (about two orders of magnitude) smaller than those measured in the field (28-72 mg/L for the Montney wells, 26-54 mg/L for the Duvernay wells). This could be attributed to the 1) dominance of the fluid mixing mechanism in the field, relative to fluid-rock interaction, 2) variable rock-water mass ratios at lab and field scales, and/or limited (initial) content of Li in the analyzed samples, amongst other factors. Lab-scale Li and Mg concentration profiles exhibited similarities to and discrepancies with those observed in the field. Notably, larger Li concentrations (up to twice) were associated with lower pH, in agreement with field observations. Interestingly, lab-scale Li and Sr concentrations appear to co-vary for the Duvernay FPW, in agreement with field observations, suggesting the possibility of using Sr as a ‘proxy element’ for predicting Li anomalies in the Duvernay FPW.\u0000 Quantifying temporal evolution of CE concentrations in FPW is essential for evaluating the feasibility of CE recovery from MFHWs and the selection of optimal Li extraction technologies over the well lifetime. This study provides the first-time comparison between lab- and field-scale temporal variations of CE concentrations in FPW for the purpose of evaluating CE extraction from unconventional hydrocarbon reservoirs.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"34 S129","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140395075","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 Quick Decline Method for Forecasting Multiple Wells Using Sparse Functional Principal Component Analysis","authors":"H. Hamdi, E. Zirbes, C. R. Clarkson","doi":"10.2118/218078-ms","DOIUrl":"https://doi.org/10.2118/218078-ms","url":null,"abstract":"\u0000 Accurate production forecasting for multiple wells that have both sparse and irregular measurements concurrently is a challenging task. Type-well analysis is commonly employed to model the average decline behavior of a group of wells from empirical relationships. The modeled type-well represents the behavior of a typical well in the studied reservoir. However, modifying the type-well to forecast individual well data is difficult. In this study, sparse functional principal component analysis (FPCA) is utilized to accurately forecast production from multiple wells simultaneously from the systematic statistical trends inferred from the group of wells.\u0000 Sparse FPCA analyzes an ensemble of irregularly-sampled timeseries to describe the underlying random process (RP) using the decomposed components. As such, one can sample from the estimated RP and generate a smooth and regularly-sampled timeseries. The sparse FPCA is primarily an interpolation method where the reconstructed timeseries could not reach beyond the horizon set by the ensemble length. However, with the proposed approach in this study, the decomposed components of FPCA are extrapolated using an autoregressive integrated moving average (ARIMA) model to generate the full probabilistic forecasts beyond the horizon. In this proposed method, the underlying RP is extrapolated first, and then the extended timeseries are generated simultaneously by sampling from the new RP. To validate the accuracy of the extrapolated data in the short-term, part of the timeseries with longer histories are excluded from the training process and only used for testing.\u0000 The sparse FPCA was applied to analyze monthly gas production data from 200 multi-fractured horizontal wells (MFHWs) of a selected operator in the Montney Formation in Canada. The results indicate that the production data of all the wells could be easily condensed using only two principal components, describing more than 99% of the information content of the production timeseries. Additionally, the resulting decomposed components were convoluted, and the production profiles of the wells with short histories were extended from the information contents of the ensemble. Additionally, with the proposed stochastic ARIMA technique, the production profiles of all the wells were forecasted for 400 months beyond the ensemble limit. The results demonstrate that the extrapolation could accurately match the measured data used for testing, which provides confidence in the stochastic long-term forecast.\u0000 This study demonstrates for the first time that sparse FPCA can be combined with the ARIMA model to quickly conduct the probabilistic production forecast for hundreds and even thousands of MFHWs simultaneously, which can significantly improve the current type-well modeling workflows.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"1 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140395116","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":"Integrated Characterization of Expanding-Solvent Steam-Assisted Gravity Drainage (ES-SAGD) Processes by Using a Heat-Penetration Criterion within a Unified, Consistent, and Efficient Framework","authors":"Shikai Yang, Daoyong Yang","doi":"10.2118/218051-ms","DOIUrl":"https://doi.org/10.2118/218051-ms","url":null,"abstract":"\u0000 The hybrid solvent-steam injection (e.g., expanding-solvent steam-assisted gravity drainage (ES-SAGD) is the most promising method to enhance heavy oil recovery (EOR); however, it is a quite a challenge to reproduce the experimental measurements and in-situ observations because of the complicated multiphase flow behaviour resulted from the coupled mass and heat transfer. In this work, an integrated technique has been developed and applied for the first time to dynamically and accurately characterize an ES-SAGD process within a unified, consistent, and efficient framework. By taking the competitive impact between heat energy and solvent dissolution, a generalized heat-penetration (HP) criterion has been derived and integrated with a numerical simulator to characterize the dynamics of solvent/steam chamber propagation conditioned to the production profiles during hybrid solvent-steam processes. This generalized HP criterion allows us to not only dynamically calculate temperature profiles beyond a solvent/steam chamber interface (SCI), but also accurately and pragmatically quantify mass and heat transfer inside the diluted oil drainage zone as well as the solvent/steam chamber. Also, comprehensive effects of the thermally sensitive co/counter-current flows are examined with a series of multiphase relative permeabilities. Such an integrated technique has been successfully validated by reproducing the measured solvent/steam chambers in 3D physical ES-SAGD experiments. Good agreements between the simulated and measured production profiles (i.e., injection temperature, pressure, and flow rate) have been made throughout the entire production period. Not only have the measured solvent/steam chambers been reproduced, but also sensitivity analyses have been performed to investigate the influences of multiphase flow behaviour, solvent concentration, and grid dimension. It is found that the diffusion/dispersion coefficients and thermal properties are dependent on temperature and solvent concentrations, competitively affecting the calculated temperature distributions. Moreover, gas-liquid relative permeabilities can impose a significant impact on the SCI moving velocity as well as the oil drainage front. Such an integrated approach considerably reduces the simulation uncertainties and complexities, offering a straightforward and effective means of dynamically reproducing the observed solvent/steam chambers within a unified, consistent, and efficient framework.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"5 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140395899","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":"Optimizing Completion Design for Delaware Basin Wells with Real-Time Performance Monitoring","authors":"A. I. Assem, A. F. Ibrahim, M. Sinkey, T. Johnston, S. Marouf","doi":"10.2118/218090-ms","DOIUrl":"https://doi.org/10.2118/218090-ms","url":null,"abstract":"\u0000 The performance of shale wells hinges significantly on the Stimulated Reservoir Volume (SRV) generated through hydraulic fracture operations, where the ratio of fluid to proppant per foot is critical for enhancing recovery. Shale well production rates are intricately tied to the Stimulated Rock Volume achieved during fracture treatments, with completion design also playing a pivotal role in optimizing SRV for individual wells.\u0000 This paper concentrates on refining completion design for Delaware Basin wells by leveraging real-time performance monitoring. The objective is to enhance overall completion design effectiveness by dynamically adjusting injected fluid volumes based on continuous monitoring of well performance. In the initial completion design for the first well on the pad, a fluid volume of 50 bbl/ft was employed. However, despite monitoring the stimulated fracture surface area, no observed fracture hits during injection and post-stage fall-off analysis suggested the potential for improvement. This led to the hypothesis that increasing the injected fluid volume to 60 bbl/ft could be beneficial.\u0000 The adjusted completion design, featuring an increased fluid volume, was implemented in the subsequent well. The stimulated surface area in these wells exceeded the initially calculated surface area in the first well, supporting the hypothesis that the increased fluid volume enhances fracture stimulation. Three months into production, the performance of the second well validated the optimized completion design. This well demonstrated higher production compared to the first, with an increase from 50 bbl/ft to 60 bbl/ft in injected fluid volume. This aligns with surface area estimations, providing tangible evidence of the advantages derived from optimizing completion design through real-time monitoring.\u0000 These findings emphasize the significance of considering stimulated surface area in the design process and underscores the crucial role of real-time well performance prediction and the adaptive adjustment of completion design parameters in maximizing production efficiency in the Delaware Basin.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140284979","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":"Pore-Scale Investigation of Caprock Integrity in Underground Hydrogen Storage","authors":"Hai Wang, Shengnan Chen, Peng Deng, Muming Wang, Zhengxiao Xu","doi":"10.2118/218099-ms","DOIUrl":"https://doi.org/10.2118/218099-ms","url":null,"abstract":"\u0000 This study investigates the sealing capacity of shale caprocks for underground storage of hydrogen (H2) utilizing mercury intrusion capillary pressure (MICP) data of caprock samples. The research explores the influence of capillary forces on gas leakage through caprocks and evaluates the effectiveness of caprocks in confining H2 and CO2. Results indicate that the interfacial tension between H2 and water/brine is significantly higher than that between CO2 and water/brine, leading to greater column heights for H2 (ranging from 59 to 667 meters) compared to CO2 (ranging from 20 to 500 meters). Additionally, the study reveals that thicker caprock layers significantly reduce the rate of gas leakage, with CO2 exhibiting higher mass leakage rates due to its larger molar mass and lower interfacial tension compared to H2. Furthermore, while the capillary bundle model estimates higher leakage rates, the pore network model, accounting for the shielding effect of small channels, predicts lower leakage rates, demonstrating its potential for more accurate estimations. The findings highlight the potential of shale caprocks as effective barriers for H2 and CO2 storage, emphasizing the importance of capillary forces and caprock thickness in mitigating gas leakage.","PeriodicalId":517551,"journal":{"name":"Day 2 Thu, March 14, 2024","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140395107","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}