Metrology and Standardization in Geomechanical Modeling - A Quantitative Assessment of Uncertainty Window Based on Calibration Data

O. Tatur, Y. Petrakov, Alexey Sobolev
{"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.
地质力学建模中的计量与标准化——基于校准数据的不确定度窗口的定量评估
地质力学建模是石油和天然气工业的一个组成部分,应用于油田的所有生命周期——监测和提高建井效率,选择完井系统,模拟水力压裂过程,模拟考虑储层应力状态变化的开发过程,考虑断层、盐构造,控制储层的开发,控制地表沉降。地质力学建模的成功与否直接取决于输入数据的数量和质量。与地质模型和水动力模型相比,地质力学模型误差的量化还没有统一的方法和算法。地质力学模型的质量定义为“满意”/“不满意”和“实际资料证实”/“实际资料未证实”。在“地质力学模型的计量支持”系列文章中,作者提出了一种定量评估地质力学模型误差的算法。提出的算法考虑了测量误差(井中和实验室)、测井数据的质量、直接测量或重建测量、相关性的紧密性(核心研究结果和缺失测井数据的重建)、考虑校准信息的不确定度计算。本文描述了以前文章中提出的一种用于量化地质力学模型误差的广义算法,并提供了一种考虑校准信息(如水平应力测量、实验室条件下的核心研究)的量化计算不确定性的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信