SPE Production & Operations最新文献

{"title":"Synthesis of Green Polyethylene Glycol-Lauric Acid Demulsifier from a Natural Source and Its Application in Demulsification of Field Emulsion: Experimental and Modeling Approach","authors":"Yogesh Dhandhi, T. Naiya","doi":"10.2118/215841-pa","DOIUrl":"https://doi.org/10.2118/215841-pa","url":null,"abstract":"\u0000 Green demulsifier was synthesized through an esterification technique by using polyethylene glycol (PEG) and fatty acid (lauric acid). The synthesized demulsifier was characterized through several tests to analyze the functional groups and determined the molecular structure, thermal stability, and biodegradability of the demulsifier molecule. The performance of the synthesized demulsifier was investigated using the standard static bottle test method to break the water-in-oil (W/O) tight emulsion. Optical microscopic and viscosity studies of emulsions were also performed to understand the demulsification process and mechanism. Based on the response surface method (RSM), central composite design (CCD) was used to develop the statistical model of demulsification efficiency by considering the four most influencing factors—demulsifier concentration, water content, settling time, and temperature—and to examine the optimal condition for maximum water separation from the emulsion. The statistical model’s accuracy and significance were evaluated using analysis of variance (ANOVA) and diagnostic plots. The effect of each factor was analyzed through 3D graphs and contour maps. The result indicates that all the factors significantly influenced the demulsification efficiency with a p-value of <0.0001, among which the presence of water is the dominating variable. At the optimal condition, the lauric acid-PEG-demulsifier (LPED) achieves a maximum demulsification efficiency of 95% in 30.9 minutes. Furthermore, the percent absolute deviation was computed after comparing the experimental findings to those predicted by the model and it was observed that the model’s prediction accuracy was >97%. Finally, the biodegradability test results showed that the developed demulsifier is completely biodegradable in 21 days. Because the synthesized demulsifier is eco-friendly and has an excellent dehydration rate, it may be used in the petroleum industry for breaking field-tight emulsions as an alternative to chemical demulsifiers.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121901054","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":"Utilizing Remote Sensing and Data Analytics Techniques to Detect Methane Emissions from the Oil and Gas Industry and Assist with Sustainability Metrics","authors":"Á. Esparza, M. Ebbs, N. De Toro Eadie, R. Roffo, L. Monnington","doi":"10.2118/215818-pa","DOIUrl":"https://doi.org/10.2118/215818-pa","url":null,"abstract":"\u0000 The purpose of this paper is to provide additional information and insights gained on manuscript SPE-209980-MS, accepted for presentation at the 2022 Society of Petroleum Engineers Annual Technical Conference and Exhibition (Esparza et al. 2022).\u0000 The energy sector has been identified as one of the main contributors to emissions of anthropogenic greenhouse gases. Therefore, sustainability in the sector is mainly associated with the advancement in environmental and social performance across multiple industries. Individual firms, particularly those belonging to the oil and gas (O&G) industry, are now assessed for their environmental, social, and governance (ESG) performance and their impact on climate change. To meet the different key performance indicators (KPIs) for corporate social responsibility (CSR) and ESG, the planning, development, and operation of O&G infrastructure must be conducted in an environmentally responsible way.\u0000 Today, operators calculate their own emissions, which are typically self-reported annually, usually relying on emission factors to complement the lack of emission measurement data. This paper discusses how methane detection of O&G infrastructure using remote sensing technologies enables operators to detect, quantify, and minimize methane emissions while gaining insights and understanding of their operations via data analytics products. The remote sensing technologies accounted for in this paper are satellite and aerial platforms operating in tandem with data analytics, providing a scheme to support sustainability initiatives through the quantification of some ESG metrics associated with methane emissions. This paper presents examples of measurements at O&G sites taken with satellites and aircraft platforms, providing evidence of methane emissions at the facility level. A discussion of each platform and how they work together is also presented. Additionally, this paper discusses how these data insights can be used to achieve sustainability goals, functioning as a tool for ESG initiatives through the incorporation of analytical models.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124436482","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":"Maximization of Gas-Oil Separation Plant Oil Recovery by Operation Parameter Optimization","authors":"Ala AL-Dogail, R. Gajbhiye, Hulail Al-Shammari, Mustafa Alnaser, Tushar Kamerkar","doi":"10.2118/215826-pa","DOIUrl":"https://doi.org/10.2118/215826-pa","url":null,"abstract":"\u0000 Maximizing oil recovery of the gas-oil separation plant (GOSP) is intended to increase revenue in the oil and gas industry. The GOSP is an integral part of the petroleum industry, and it consists of multistage separators, a heater-treater, desalination, a stabilization column, and a stock tank of oil. It is conventional practice to operate the GOSP at fixed operating conditions without considering the effects of variation for different parameters such as ambient temperature, chemical composition, reboiler (60°C, 65°C, and 70°C), and stabilization (temperature and pressure). Optimizing the GOSP parameters can help to maximize the GOSP oil recovery and, as a result, increase the revenue and profit.\u0000 This study aims to optimize operation parameters to maximize the oil recovery of the GOSP at which the maximum oil recovery can be obtained from the GOSP. To achieve the objective of this study, first, a GOSP model was built using Petro-SIM process simulator software for a typical Saudi Aramco GOSP. The input data for the process simulator were the data from the initial pressure/volume/temperature (PVT) analysis. Optimizer tools in Petro-SIM were used to estimate the optimal conditions of the GOSP for achieving maximum oil recovery.\u0000 The results showed that the optimization of the GOSP parameters such as ambient temperature, high-pressure separator (HPS), low-pressure separator (LPS), reboiler temperature, and stabilization pressure and temperature have a significant effect on the GOSP oil recovery and lead to increased revenues. Adjusting the HPS and LPS pressures to the optimal values at each ambient temperature significantly improves the GOSP oil recovery and can generate extra revenue of more than USD 500 million for 3 months considering the typical climate condition and GOSP (50,000 B/D capacity) in Saudi Arabia.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"1210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125984213","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":"Data-Driven Analysis of Stimulation Treatments Using Association Rule Mining","authors":"Rouholah Ahmadi, B. Aminshahidy, J. Shahrabi","doi":"10.2118/214699-pa","DOIUrl":"https://doi.org/10.2118/214699-pa","url":null,"abstract":"\u0000 Effective analysis of data collected during the well’s operational cycle is crucial to well performance, economic evaluation, and good decision-making in the upstream oil industry. Generally, the analysis of huge volumes of data stored in databases is beyond the power of traditional methods, such as curve-fitting and statistical hypothesis testing. Data mining is the practice of analyzing large databases to identify patterns, anomalies, and correlations, within the data, leading to new, hidden, and valuable knowledge that would support decisions. This article proposes a data-driven methodology for analyzing the stimulation operations data in oil/gas wells to identify the underlying rules or patterns that lead to successful operations. Association rule mining (ARM) is used in this research for rule induction purposes. The proposed approach aims to mine the frequently occurring rules, within the collected database, that guarantee the success of stimulation operations with a high degree of confidence. Finally, the proposed approach is evaluated against a set of real data from an Iranian oil field. On the basis of past stimulation operations, these extracted rules show the conditions that are most likely to lead to a successful operation. The rules identified by the proposed approach are compared against the rules that can be generated by the decision tree (DT) technique using the same data set. As the reliability of the rules is controlled by setting the minimum thresholds on support and confidence, more significant and useful rules could be derived from ARM compared to the DT technique. Using the identified rules and generated information can support the operational decisions by assisting in the design of due stimulation jobs or in selecting the appropriate candidates for future operations.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123170757","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":"Methane Emissions Quantification and Resulting Methane Emissions Reduction in the Permian Basin Enabled by Automated Unmanned Systems","authors":"Jason Churchill, Brenda Wise, Iain Cooper, Brendan Smith","doi":"10.2118/210173-pa","DOIUrl":"https://doi.org/10.2118/210173-pa","url":null,"abstract":"\u0000 Traditional methods for monitoring emissions from production operations have typically used optical gas imaging cameras or Method 21 systems, based on an intermittent basis to determine and document methane gas leaks, which are then subsequently identified for repair under the US Code of Federal Regulations (2017). These optical gas imaging emissions monitoring surveys can have a subjective bias, are highly conditional on the skill of the camera operator, and are an inexact method of measuring the quantity of the leak rate. With a renewed industry emphasis on methane emissions measurement and reduction, this paper describes a case study using a high-sensitivity sensor technology (laser absorption spectrometry) specifically targeting methane emissions, the unique capabilities engendered by its deployment on unmanned aerial systems (UAS), the leveraging of automation in field-operation and data analysis, and the system’s successful utilizationin enabling emissions limitations over several production sites in the Permian Basin.\u0000 The use of automation enabled categorization of the leak type and intensity, and triage according to leak rate, facilitating prompt remedial action and directly limiting emissions. By automating the comprehensive flight paths specific to equipment groups (e.g., compressors, tanks, and flares), targeted repeat surveys confirmed that specific leaks were fixed, emphasizing a general downward trend in overall site- and asset-level emissions. These surveys were completed in 22.5 minutes, on average, at each of the five sites. Additionally, the use of high-resolution UAS-generated orthomosaic maps enabled the direct placement of emissions data into the context of the operations at the time of the survey, facilitating the generation of automated actionable reports, helping direct repair teams, and resulting in effective and necessary fixes. Furthermore, the campaign validated that following the set up of the initial survey, subsequent regular, repeat surveys could be commissioned at the “push of a button,” yielding reliable, actionable emissions data, with a direct impact on both environmental (6% reduction in emissions) and financial impact.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130737170","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":"Continuous Methane Monitoring: Equivalency Evaluation of Regulator-Approved Alternative Leak Detection and Repair Program in Alberta, Canada","authors":"Tim Benko, A. Macgregor, Eric Wen, Thomas Fox, B. Moorhouse","doi":"10.2118/209973-pa","DOIUrl":"https://doi.org/10.2118/209973-pa","url":null,"abstract":"\u0000 Diverse methods have emerged for methane leak detection and repair (LDAR), alongside a growing interest in continuous monitoring (CM). Novel LDAR programs must demonstrate equivalent (or better) emissions reductions compared to conventional handheld methods to be approved by regulators and trusted by industry. We apply and test a widely accepted equivalency framework and report on a regulatory approved alternative LDAR pilot program to evaluate the performance of CM relative to conventional LDAR. The framework, which has not been formally tested to date, relies on a combination of controlled release testing, simulation modeling, and field piloting. First, controlled release testing at known emission rates is used to establish probability of detection functions and other performance metrics for the CM device. Performance metrics are then used to build a CM module in LDAR Simulator (LDAR-Sim), an open-access modeling framework. Finally, CM devices are deployed as part of a field pilot.\u0000 Controlled release testing results and dispersion modeling suggest that the CM devices can reliably detect (i.e., 90% detection probability or greater) a rate of 1 kg/h (~54 scf/hr) from distances of 75–100 m with no false positive detections. A set of work practices were established using the LDAR-Sim framework. The CM program requires close-range follow-up for any detection event and is estimated by LDAR-Sim to reduce aggregate annual fugitive methane emissions by 91.8% relative to the baseline, doubling the reductions anticipated from a conventional regulatory program. For the pilot, 52 devices are deployed across 16 facilities with Enhance Energy. All devices are positioned within 100 m of monitored assets. Each time devices record a detection event, which is defined as a sustained anomaly three standard deviations above a moving average background concentration for 24 hours, 7 days, or 60 days, the operator performs a close-range follow-up inspection. Preliminary results show that the CM devices can detect leaks and that follow-up protocols are effective at immediately finding leaks and avoiding false positives. Confirmed detections include fugitive emissions such as a tank thief hatch leak and vented emissions including high-bleed pneumatics. Both types of emissions were confirmed as repaired or improved by CM. These results indicate that repairing leaks more expeditiously through faster detection can reduce emissions by up to 90%.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125142829","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":"Investigating the Mean Residence Time in a Two-Phase Oil-Water Separator Using Volume of Fluid Multiphase Theory in Computational Fluid Dynamics Simulation","authors":"","doi":"10.2118/214687-pa","DOIUrl":"https://doi.org/10.2118/214687-pa","url":null,"abstract":"\u0000 Multiphase separators are essential to chemical units, especially in the oil and gas industry. Because separators are usually the first equipment installed in the oil and gas units, their performance directly affects other equipment. A two-phase oil-water separator was investigated in this study. Based on the average residence time reported for the pilot separator, the computational fluid dynamics (CFD) simulation was validated. The multiphase volume of fluid (VOF) theory in Ansys Fluent software is used for the simulation. Initially, the effect of halving the geometry from its line of symmetry was investigated to see if the halved geometry could replace the complete geometry in the simulation. After validation, the effect of four different inlet deflectors on the mean residence time (MRT) was investigated. A spherical inlet deflector and three plate inlet deflectors with varying angles were tested to examine the effects of inlet deflectors. Among the plate inlet deflectors, the one with an angle between the plates of 105 degrees had the highest MRT and the separator with an angle between the plates of 135 degrees had the lowest MRT. This is because of the fluid conduction by the separator and its collision with its wall. The spherical input deflector increases the MRT by 8.9% compared to the separator without the input deflector.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127706889","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":"Leak Detection in Natural Gas Pipelines Based on Unsupervised Reconstruction of Healthy Flow Data","authors":"Jing Liang, Shan Liang, Hao Zhang, Zhonglin Zuo, Li Ma, Juan Dai","doi":"10.2118/214686-pa","DOIUrl":"https://doi.org/10.2118/214686-pa","url":null,"abstract":"\u0000 Timely detection of leak accidents plays an essential role in the safe operation and risk assessment of natural gas pipelines. However, the scarce leak data and complex operating conditions lead to small samples, data imbalance, and problems with confusing operating conditions. The reliance on leak data limits the recognition performance of the artificial intelligence classification method for leakage operating conditions. A leak detection method based on the unsupervised reconstruction of healthy flow data is established to address these problems. First, an unsupervised neural network is established to reconstruct healthy flow data from real natural gas pipelines. And a model update strategy based on active learning is designed to improve the model’s adaptability for time-varying pipelines. Next, a dynamic alarm threshold strategy that accounts for the knowledge of the experience and statistical characteristics of the data segments is suggested to prevent false alarms caused by ambiguous operating conditions. Finally, unlike most recent work that only considers simulated data or laboratory data, this paper conducts a leak case study on an actual natural gas pipeline in service to improve the robustness of the proposed method in the actual operating environment. The findings of this paper can be used as a reference to analyze pipeline behavior analysis based on pipeline flow trend characteristics and early alarm management.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128012563","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":"Experimental Investigation on the Performance of Polymer-Coated Clay/Polyacrylamide Hydrogel for Water Shutoff Treatment","authors":"A. Roslan, N. Aziz, I. Dzulkarnain, R. Tewari, M. Jaafar","doi":"10.2118/214662-pa","DOIUrl":"https://doi.org/10.2118/214662-pa","url":null,"abstract":"\u0000 Polymer gel system has been identified as having the potential for blocking and diverting water flow. However, the current polymer reported an inability to maintain its mechanical strength, limited penetration depth, and instability in reservoir conditions of high temperature and high pressure. A distinctive bentonite nanomer clay (PGV)/acrylamide (AM)-co-2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS) preformed particle gel with poly(ethylene glycol-b-tetramethylene oxide) (PEGTMO) coating to control the swelling kinetics is formulated. The in-house formulated gel’s ability to block and divert water flow in a porous medium is studied. The formation recipe of the gel was achieved by numerous swelling tests as induced by brine solution under reservoir conditions. Through the swelling tests, the long-term thermal stability of the gel solution was demonstrated. The incorporation of PGV clay particles improves the swelling and mechanical properties of the gel. Premature swelling can be avoided with PEGTMO coating as it slows the swelling rate over a 10-minute period, which gives the advantage of controlling the swelling before reaching the intended site of action during coreflood experiments. The rheological behavior of the hydrogel features rubber-like mechanical behavior with a viscosity value of 1.17 cp, which displayed water-like characteristics. Further, significant permeability reduction of large fractures is demonstrated by the coreflooding experiment with a calculated result of 96.2%. This formulated gel could offer the solution as a blocking agent in void space channels containing reservoirs that leads to a reduction of water cut due to thief zones.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128232650","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":"Evaluation of Parent Well Depletion Effects on Fracture Geometry Based on Low-Frequency Distributed Acoustic Sensing in Hydraulic Fracture Test Site-2","authors":"Aishwarya Srinivasan, Joe Mjehovich, Wen Wang, Kan Wu, G. Jin, G. Moridis","doi":"10.2118/212344-pa","DOIUrl":"https://doi.org/10.2118/212344-pa","url":null,"abstract":"\u0000 Low-frequency distributed acoustic sensing (LF-DAS) has recently received much attention for its ability to monitor fracture propagation at offset wells. Hydraulic Fracture Test Site-2 (HFTS-2), a Department of Energy–sponsored field-based research experiment, has acquired LF-DAS data sets during the stimulation of many horizontal wells in the Wolfcamp Formation of the Permian Basin. Over 100 stimulated stages with different completion designs in four horizontal wells were monitored by two horizontal offset wells and one vertical pilot hole with permanent fibers. The parent well depletion affected all four horizontal wells in almost half of their lateral section. Several studies have been performed on the acquired comprehensive data set. In this study, we apply our novel Green’s function-based inversion algorithm to calculate the fracture width of each stage and investigate the impact of parent well depletion on fracture geometry. The Green’s function-based inversion algorithm has been successfully applied to a few stages of field case studies. The Green’s function matrix was built based on linear elasticity theory (3D displacement discontinuity method) to relate the fracture openings with strain responses measured along the length of the fiber. This novel algorithm only relies on measured strain to solve fracture geometry at the monitoring well. Therefore, it is independent of the physics of the fracture propagation process and can be used to validate hydraulic fracture modeling results. Using our inversion algorithm, we can efficiently and quantitatively interpret LF-DAS data to provide information on fracture geometry and completion efficiency.\u0000 We analyze more than 100 stages of the LF-DAS measurements obtained at the fiber wells B3H and B4H during B1H, B2H, and B4H stimulations. We apply our inversion algorithm for four data sets covering the stimulation of the abovementioned three wells. The fracture growth at stages in the parent well’s depleted zone is biased more toward upper formation and in the easterly direction. The fracture width at the stages in the parent well’s depletion zone is reduced compared to fracture widths at stages in the nondepleted zone irrespective of the monitoring well location relative to the treatment wells. This difference in fracture widths will affect the proppant distribution to a great extent, thereby affecting the effectiveness of the stimulation. We also illustrate the application of the inversion algorithm for stages that have both conventional fracture hits with “heart-shaped” signals as well as fracture reopening signals. Our inversion algorithm gives a reasonable estimate of the fracture width that aligns with the qualitative analysis of microseismic data sets and statistic summary of fracture hit numbers of HFTS-2. We believe that this quantitative study provides us with insights into the fracture geometry due to parent well depletion effects.","PeriodicalId":153181,"journal":{"name":"SPE Production &amp; Operations","volume":"302 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116598537","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}