Journal of Petroleum Exploration and Production Technology最新文献

{"title":"A modified cell-to-cell simulation model to predict oil-gas minimum miscibility pressure","authors":"FuLin Yang","doi":"10.1007/s13202-024-01839-y","DOIUrl":"https://doi.org/10.1007/s13202-024-01839-y","url":null,"abstract":"","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141849342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the vaporization mechanism's effect on interfacial tension during gas injection into an oil reservoir","authors":"Hossein Mehrjoo, Ali Safaei, Yousef Kazemzadeh, Masoud Riazi, Atefe Hasan-zadeh","doi":"10.1007/s13202-024-01821-8","DOIUrl":"https://doi.org/10.1007/s13202-024-01821-8","url":null,"abstract":"<p>In gas injection, which is one of the fascinating enhanced oil recovery techniques, the main mechanism involves decreasing interfacial tension (IFT). Although various mechanisms can affect the IFT of a system, in most experimental and numerical studies, condensation is considered the dominant mechanism among condensation-vaporization and vaporization. Investigating the impact of each mechanism is crucial as they can influence the IFT of the system and, consequently, the effectiveness of the gas injection method. This study introduces a novel model to assess the influence of different mechanisms on system IFT. The model defines system IFT, adjusts fluid relative permeability to represent miscible, immiscible, and near-miscible states, and utilizes the Buckley–Leverett method to analyze gas fractional flow and saturation profiles when injecting carbon dioxide (CO₂), methane (CH₄), and nitrogen (N₂). Furthermore, the research explores the impact of injection pressure and IFT at minimum miscible pressure (IFT0) on gas injection efficiency. Based on our results, for both live and dead oil, the condensation mechanism reduces IFT and near-miscible pressure; switching to a condensing-vaporizing mechanism increases these parameters. This trend was consistent across all gases studied (N₂, CO₂, CH₄), with a more significant effect observed on the CH₄-live oil system compared to N₂ and CO₂. Controlling the condensing mechanism in IFT measurements enhances gas flow rate and relative permeability curve within the medium. Higher injection pressure in the condensing mechanism and IFT0 = 0.5 leads to faster fluid movement and improved relative permeability due to increased driving forces. Higher IFT0 accelerates the relative permeability of fluids and gas movement within the medium by promoting miscibility sooner. The impact of IFT0 was more pronounced on the dead oil–gas system compared to the live oil–gas system in this study.</p>","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141254906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing cluster spacing in multistage hydraulically fractured shale gas wells: balancing fracture interference and stress shadow impact","authors":"Ahmed Farid Ibrahim","doi":"10.1007/s13202-024-01831-6","DOIUrl":"https://doi.org/10.1007/s13202-024-01831-6","url":null,"abstract":"<p>Horizontal drilling and multistage hydraulic fracturing have seen widespread application in shale formations during the past decade, leading to significant economic productivity gains through the creation of extensive fracture surfaces. The determination of the ideal cluster spacing in shale gas wells is contingent upon the unique geological and formation characteristics. Generally, reducing the spacing between clusters has the potential to augment gas recovery, albeit at the expense of higher drilling and completion costs, as well as the influence of stress shadows on fracture propagation. This study introduces an integrated methodology designed to explore the impact of cluster interference on well performance. Commencing with a fracture propagation model accommodating stress shadow effects for an equivalent slurry volume injection, analytical rate transient analysis (RTA) was amalgamated with reservoir numerical simulation to compute the effective fracture surface area (A_ca.) for hydrocarbon production. The correlation between the effective fracture surface area determined by RTA and the actual stimulated fracture area (A_ca.) derived from numerical simulations was established in relation to cluster spacing. The findings of this research reveal that wells featuring a greater number of stages and tighter cluster spacing tend to exhibit elevated cluster interference, resulting in a lower effective-to-actual fracture surface area ratio and heightened stress shadow effects impeding fracture propagation. A cluster spacing of 33 feet with six clusters per stage emerges as the optimal choice at formation permeability of 0.00005 md that decreased to 18 ft at formation permeability of 0.00001 md. A_Ce either stabilizes or decreases above the optimal value, suggesting that more clusters would not have a major impact on increasing the effective stimulated area. Allowing 20% interference, regardless of the permeability of the formation, maximized cumulative production while preventing thief zones and excessive cluster interference. The insights gained from this study will serve as a valuable resource for completion and reservoir engineers, enabling them to fine-tune cluster spacing to maximize well revenue in the dynamic landscape of shale gas extraction.</p>","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141197048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of artificial intelligence to predict rock strength and drilling efficiency using in-cutter sensing data and vibration modes","authors":"Alexis Koulidis, Guang Ooi, Shehab Ahmed","doi":"10.1007/s13202-024-01823-6","DOIUrl":"https://doi.org/10.1007/s13202-024-01823-6","url":null,"abstract":"<p>Drilling is a complex destructive action that induces vibrations due to the rock-bit interaction, which affects the overall drilling efficiency and wellbore quality. This study aims to enhance drilling efficiency by deploying artificial neural networks (ANNs) to integrate in-cutter force sensing and vibration data. Data is collected from experiments conducted with sharp cutters on rock samples of varying mechanical properties, measuring variables such as weight on bit, torque, rotational speed, in-cutter force, and vibration measurements. A scoring system is used to evaluate the drilling efficiency by coupling the mechanical specific energy and vibration modes. An ANN is trained with these variables to predict the rate of penetration and rock strength, which are also measured in the experiments to be used as ground truth. The reliability of the framework is demonstrated by testing the validity of the ANN model on samples with various mechanical properties. It introduces a reliable and swift method for determining optimal drilling parameters, supported by a sensitivity analysis to fine-tune the ANN and assess the influence of each parameter on performance. This study demonstrates that ANN could be successfully implemented to predict the rate of penetration and rock strength on a laboratory-scaled drilling rig. The results show that the ANN model accurately predicts training and testing datasets for scoring while drilling multiple layers with a correlation coefficient of 0.966. Integration of in-cutter sensing technology, vibration data, and ANN can be of significant interest and be used on field applications to provide a reliable and rapid decision about drilling efficiency.</p>","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141197378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental design and manufacturing of a smart control system for horizontal separator based on PID controller and integrated production model","authors":"Mehdi Fadaei, Mohammad Javad Ameri, Yousef Rafiei, Morteza Asghari, Mehran Ghasemi","doi":"10.1007/s13202-024-01824-5","DOIUrl":"https://doi.org/10.1007/s13202-024-01824-5","url":null,"abstract":"<p>During oil production, the reservoir pressure declines, causing changes in the hydrocarbon components. To ensure better separation of produced phases, separator dimensions should also be adjusted. It is not possible to change the dimensions of the separator during production. Therefore, to improve the separation of the phases, the level of the separator needs to be adjusted. An intelligent system is required to ensure that the liquid level is maintained at the desired level for optimal phase separation during changes in reservoir pressure. In this study, a novel correlation is presented to measure the desired liquid level using new separator pressures. For this purpose, an intelligent system was built in the laboratory and tested in different operational conditions. The intelligent system effectively maintained the desired liquid level of the separator through a new correlation technique. The system accomplished this by acquiring new separator pressure readings collected by installed sensors. This approach helped mitigate the negative effects of the slug flow regime and minimized issues such as foam formation and over-flushing of the separator. It could achieve a 99.1% separation efficiency between gas and liquid phases. This was possible during liquid and gas flow rates ranging from 0 to 2.35 and 8–17 m³/h, respectively. The system could operate under bubble, stratified, plug, and slug flow regimes. Then the intelligent model obtained from lab experiments was integrated into the production model for the southern Iranian oil field. The smart model increased oil production by 13% and prevented the separator from over-flushing in 840 days.</p>","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141197176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relative permeability estimation using mercury injection capillary pressure measurements based on deep learning approaches","authors":"Ce Duan, Bo Kang, Rui Deng, Liang Zhang, Lian Wang, Bing Xu, Xing Zhao, Jianhua Qu","doi":"10.1007/s13202-024-01826-3","DOIUrl":"https://doi.org/10.1007/s13202-024-01826-3","url":null,"abstract":"<p>Relative permeability (RP) curves which provide fundamental insights into porous media flow behavior serve as critical parameters in reservoir engineering and numerical simulation studies. However, obtaining accurate RP curves remains a challenge due to expensive experimental costs, core contamination, measurement errors, and other factors. To address this issue, an innovative approach using deep learning strategy is proposed for the prediction of rock sample RP curves directly from mercury injection capillary pressure (MICP) measurements which include the mercury injection curve, mercury withdrawal curve, and pore size distribution. To capture the distinct characteristics of different rock samples' MICP curves effectively, the Gramian Angular Field (GAF) based graph transformation method is introduced for mapping the curves into richly informative image forms. Subsequently, these 2D images are combined into three-channel red, green, blue (RGB) images and fed into a Convolutional Long Short-Term Memory (ConvLSTM) model within our established self-supervised learning framework. Simultaneously the dependencies and evolutionary sequences among image samples are captured through the limited MICP-RP samples and self-supervised learning framework. After that, a highly generalized RP curve calculation proxy framework based on deep learning called RPCDL is constructed by the autonomously generated nearly infinite training samples. The remarkable performance of the proposed method is verified with the experimental data from rock samples in the X oilfield. When applied to 37 small-sample data spaces for the prediction of 10 test samples, the average relative error is 3.6%, which demonstrates the effectiveness of our approach in mapping MICP experimental results to corresponding RP curves. Moreover, the comparison study against traditional CNN and LSTM illustrated the great performance of the RPCDL method in the prediction of both <i>S</i>_<i>o</i> and <i>S</i>_<i>w</i> lines in oil–water RP curves. To this end, this method offers an intelligent and robust means for efficiently estimating RP curves in various reservoir engineering scenarios without costly experiments.</p>","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141197437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility analysis of commingle production of multi-layer reservoirs in the high water cut stage of oilfield development","authors":"Xueqi Liu, Han Qi, Jian Liu, Xiaoyan Geng, Kexin Zhang, Yunbo Li","doi":"10.1007/s13202-024-01773-z","DOIUrl":"https://doi.org/10.1007/s13202-024-01773-z","url":null,"abstract":"","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141120061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Critical pressure (Pc) and critical temperature (Tc) of Midra shale","authors":"Mehdi Alipour, A. Sakhaee-Pour","doi":"10.1007/s13202-024-01807-6","DOIUrl":"https://doi.org/10.1007/s13202-024-01807-6","url":null,"abstract":"","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141119681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Laboratory investigation on inhibition of polyvinyl alcohol used for wireline coring drilling","authors":"Yuming Huang, Wenlong Zheng, Guoqi Zhang, Yong Chen, Jiashuo Qin","doi":"10.1007/s13202-024-01819-2","DOIUrl":"https://doi.org/10.1007/s13202-024-01819-2","url":null,"abstract":"","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141121050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust fracture intensity estimation from petrophysical logs and mud loss data: a multi-level ensemble modeling approach","authors":"Ahmad Azadivash, Hosseinali Soleymani, Atrina Seifirad, Amirali Sandani, Farshid Yahyaee, A. Kadkhodaie","doi":"10.1007/s13202-024-01820-9","DOIUrl":"https://doi.org/10.1007/s13202-024-01820-9","url":null,"abstract":"","PeriodicalId":16723,"journal":{"name":"Journal of Petroleum Exploration and Production Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}