Marcellus Shale Energy and Environmental Laboratory (MSEEL) Results and Plans: Improved Subsurface Reservoir Characterization And Engineered Completions
T. Carr, P. Ghahfarokhi, B. Carney, Jay Hewitt, Robert Vargnetti
{"title":"Marcellus Shale Energy and Environmental Laboratory (MSEEL) Results and Plans: Improved Subsurface Reservoir Characterization And Engineered Completions","authors":"T. Carr, P. Ghahfarokhi, B. Carney, Jay Hewitt, Robert Vargnetti","doi":"10.15530/URTEC-2019-415","DOIUrl":null,"url":null,"abstract":"The Marcellus Shale Energy and Environment Laboratory (MSEEL) involves a multidisciplinary and multi-institutional team of universities companies and government research labs undertaking geologic and geomechanical evaluation, integrated completion and production monitoring, and testing completion approaches. MSEEL consists of two legacy horizontal production wells, two new logged and instrumented horizontal production wells, a cored vertical pilot bore-hole, a microseismic observation well, and surface geophysical and environmental monitoring stations. The extremely large and diverse (multiple terabyte) datasets required a custom software system for analysis and display of fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) data that was subsequently integrated with microseismic data, core data and logs from the pilot holes and laterals. Comprehensive geomechanical and image log data integrated with the fiber-optic data across individual stages and clusters contributed to an improved understanding of the effect of stage spacing and cluster density practices across the heterogeneous unconventional reservoirs such as the Marcellus. The results significantly improved stimulation effectiveness and optimized recovery efficiency. The microseismic and fiber-optic data obtained during the hydraulic fracture simulations and subsequent DTS data acquired during production served as constraining parameters to evaluate stage and cluster efficiency on the MIP3H and MIP-5H wells. Deformation effects related to preexisting fractures and small faults are a significant component to improve understanding of completion quality differences between stages and clusters. The distribution of this deformation and cross-flow between stages as shown by the DAS and DTS fiber-optic data during stimulation demonstrates the differences in completion efficiency among stages. The initial and evolving production efficiency over the last several years of various stages is illustrated through ongoing processing of continuous DTS. Reservoir simulation and history matching the well production data confirmed the subsurface production response to the hydraulic fractures. Engineered stages that incorporate the distribution of fracture swarms and geomechanical properties had better completion and more importantly production efficiencies. We are working to improve the modeling to understand movement within individual fracture swarms and history match at the individual","PeriodicalId":432911,"journal":{"name":"Proceedings of the 7th Unconventional Resources Technology Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 7th Unconventional Resources Technology Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15530/URTEC-2019-415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The Marcellus Shale Energy and Environment Laboratory (MSEEL) involves a multidisciplinary and multi-institutional team of universities companies and government research labs undertaking geologic and geomechanical evaluation, integrated completion and production monitoring, and testing completion approaches. MSEEL consists of two legacy horizontal production wells, two new logged and instrumented horizontal production wells, a cored vertical pilot bore-hole, a microseismic observation well, and surface geophysical and environmental monitoring stations. The extremely large and diverse (multiple terabyte) datasets required a custom software system for analysis and display of fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) data that was subsequently integrated with microseismic data, core data and logs from the pilot holes and laterals. Comprehensive geomechanical and image log data integrated with the fiber-optic data across individual stages and clusters contributed to an improved understanding of the effect of stage spacing and cluster density practices across the heterogeneous unconventional reservoirs such as the Marcellus. The results significantly improved stimulation effectiveness and optimized recovery efficiency. The microseismic and fiber-optic data obtained during the hydraulic fracture simulations and subsequent DTS data acquired during production served as constraining parameters to evaluate stage and cluster efficiency on the MIP3H and MIP-5H wells. Deformation effects related to preexisting fractures and small faults are a significant component to improve understanding of completion quality differences between stages and clusters. The distribution of this deformation and cross-flow between stages as shown by the DAS and DTS fiber-optic data during stimulation demonstrates the differences in completion efficiency among stages. The initial and evolving production efficiency over the last several years of various stages is illustrated through ongoing processing of continuous DTS. Reservoir simulation and history matching the well production data confirmed the subsurface production response to the hydraulic fractures. Engineered stages that incorporate the distribution of fracture swarms and geomechanical properties had better completion and more importantly production efficiencies. We are working to improve the modeling to understand movement within individual fracture swarms and history match at the individual