将基于知识的技术整合到试井解释中

I. Harrison, J. Fraser
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引用次数: 0

摘要

Spirit项目的目标是开发下一代井试解释(WTI)软件的原型,该软件将为WTI模型选择任务提供基于知识的决策支持。本文描述了Spirit如何利用几种不同类型的信息(压力、地震、岩石物理、地质和工程)来支持用户识别最合适的WTI模型。Spirit基于知识的类型曲线匹配方法是,通过假设井筒储存和后期边界效应的可能存在,生成几种不同的可行解释。Spirit通过使用与WTI专家合作开发的基于知识的决策模型,融合了来自类型曲线匹配和其他数据源的信息。这项工作的发起人认为最终的原型系统是成功的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating Knowledge-Based Techniques Into Well Test Interpretation
The goal of the Spirit Project was to develop a prototype of next-generation well-test-interpretation (WTI) software that would include knowledge-based decision support for the WTI model selection task. This paper describes how Spirit makes use of several different types of information (pressure, seismic, petrophysical, geological, and engineering) to support the user in identifying the most appropriate WTI model. Spirit`s knowledge-based approach to type-curve matching is to generate several different feasible interpretations by making assumptions about the possible presence of both wellbore storage and late-time boundary effects. Spirit fuses information from type-curve matching and other data sources by use of a knowledge-based decision model developed in collaboration with a WTI expert. The sponsors of the work have judged the resulting prototype system a success.
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