{"title":"Metrology and Standardization in Geomechanical Modeling - A Quantitative Assessment of Uncertainty Window Based on Calibration Data","authors":"O. Tatur, Y. Petrakov, Alexey Sobolev","doi":"10.2118/206564-ms","DOIUrl":null,"url":null,"abstract":"\n Geomechanical modeling is an integral part of the oil and gas industry and is used in all life cycles of the field - monitoring and improving the efficiency of well construction, choosing a completion system, modeling hydraulic fracturing processes, modeling development processes taking into account changes in the stress state of the reservoir, taking into account the fault, salt tectonics, control over the development of the reservoir, control of subsidence of the earth's surface. The success of geomechanical modeling directly depends on the quantity and quality of input data. In contrast to the geological and hydrodynamic models, in geomechanics there is still no unified approach and algorithm for quantifying the model error. The quality of the geomechanical model is defined as \"satisfactory\" / \"not satisfactory\" and \"confirmed by actual data\" / \"not confirmed by actual data\". In a series of articles on \"Metrological support of a geomechanical model\", the authors show an algorithm for a quantitative assessment of the error of a geomechanical model. The proposed algorithm takes into account the measurement error (in the well and in the laboratory), the quality of logging data, direct measurements or reconstructed measurements, the tightness of correlations (both for the results of core studies and for the reconstruction of missing logging data), the calculation of the uncertainty taking into account the calibration information.\n This paper describes a generalized algorithm for quantifying the error of a geomechanical model, presented in previous articles, and provides a method for quantifying calculate the uncertainty, taking into account calibration information, such as measurements of horizontal stresses, core studies in laboratory conditions.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":"80 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Wed, October 13, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/206564-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Geomechanical modeling is an integral part of the oil and gas industry and is used in all life cycles of the field - monitoring and improving the efficiency of well construction, choosing a completion system, modeling hydraulic fracturing processes, modeling development processes taking into account changes in the stress state of the reservoir, taking into account the fault, salt tectonics, control over the development of the reservoir, control of subsidence of the earth's surface. The success of geomechanical modeling directly depends on the quantity and quality of input data. In contrast to the geological and hydrodynamic models, in geomechanics there is still no unified approach and algorithm for quantifying the model error. The quality of the geomechanical model is defined as "satisfactory" / "not satisfactory" and "confirmed by actual data" / "not confirmed by actual data". In a series of articles on "Metrological support of a geomechanical model", the authors show an algorithm for a quantitative assessment of the error of a geomechanical model. The proposed algorithm takes into account the measurement error (in the well and in the laboratory), the quality of logging data, direct measurements or reconstructed measurements, the tightness of correlations (both for the results of core studies and for the reconstruction of missing logging data), the calculation of the uncertainty taking into account the calibration information.
This paper describes a generalized algorithm for quantifying the error of a geomechanical model, presented in previous articles, and provides a method for quantifying calculate the uncertainty, taking into account calibration information, such as measurements of horizontal stresses, core studies in laboratory conditions.