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您的检索式：作者名="Temoor Muther"
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| 1 | Laboratory to field scale assessment for EOR applicability in tight oil reservoirs显示文摘Tight oil reservoirs are contributing a major role to fulfill the overall crude oil needs,especially in the US.However,the dilemma is their ultra-tight permeability and an uneconomically short-lived primary recovery factor.Therefore,the application of EOR in the early reservoir development phase is considered effective for fast-paced and economical tight oil recovery.To achieve these objectives,it is imperative to determine the optimum EOR potential and the best-suited EOR application for every individual tight oil reservoir to maximize its ultimate recovery factor.Since most of the tight oil reservoirs are found in wide spatial source rock with complex and compacted pores and poor geophysical properties yet they hold high saturation of good quality oil and therefore,every single percent increase in oil recovery from such huge reservoirs potentially provide an additional million barrels of oil.Hence,the EOR application in such reservoirs is quite essential.However,the physical understanding of EOR applications in different circumstances from laboratory to field scale is the key to success and similarly,the fundamental physical concepts of fluid flow-dynamics under confinement conditions play an important role.This paper presents a detailed discussion on laboratory-based experimental achievements at micro-scale including fundamental concepts under confinement environment,physics-based numerical studies,and recent actual field piloting experiences based on the U.S.unconventional plays.The objective of this paper is to discuss all the critical reservoir rock and fluid properties and their contribution to reservoir development through massive multi-staged hydraulic fracture networks and the EOR applications.Especially the CO_(2)and produced hydrocarbon gas injection through single well-based huff-n-puff operational constraints are discussed in detail both at micro and macro scale. | Fahad Iqbal Syed Amirmasoud Kalantari Dahaghi Temoor Muther | 2022 | Petroleum Science2022，19，5： | 2 |
| 2 | Smart shale gas production performance analysis using machine learning applications显示文摘With the advancement of technology and innovation in the oil and gas industry,the production of liquid and gaseous hydrocarbon from conventional and unconventional resources has seen exponential growth.Recently,the USA and other oil giants have shifted their paradigm from conventional to unconventional resources of exploration and production of hydrocarbon.However,there is still a perpetual force that exists to develop and devise new innovative approaches and methodologies for the exploration,extraction efficiencies,and production performance of hydrocarbons.To better evaluate the impact of well attributes,reservoir characteristics and production behavior of well machine learning and artificial intelligence-based models have been developed by researchers that with the help of simulation and modeling provide us the true picture of reservoir performance without exploring and investing billions of dollars.This review paper encompasses the literature published in the recent years and narrated the recent development made by researchers especially in the field of production performance estimation of shale gas by developing machine learning-based models.More specifically,this paper deals with the major shale gas reservoir of North America including Marcellus shale,Eagle Ford shale,and Bakken Shale.Additionally,equations,input parameters,and formations that are considered key parameters for the development of the smart shale gas models are also discussed in this manuscript.In addition,the methodology comparison of different machine learning algorithms including their limitations and advantages are also presented. | Fahad I.Syed Salem Alnaqbi Temoor Muther Amirmasoud K.Dahaghi Shahin Negahban | 2022 | Petroleum Research2022，7，1： | 0 |
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