自动化和精确的井位在降低地下复杂性和优化地质导向中的作用——以复杂非常规油藏为例

Kalyan Saikia, Narayan H. Shanker
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引用次数: 1

摘要

随着对油气需求的不断增加,非常规油气藏日益突出,在油气产量中占很大比例。然而,这些非常规油藏不可避免地面临着一些挑战,在制定开采策略以获得最大采收率时,必须仔细管理这些挑战。本文展示了集成和自动化的井位工作流程的优势,以提高复杂非常规油藏的地质导向,最大限度地提高油气采收率。自动化配井技术由三个主要组成部分控制:(1)综合资产模型;(2)可获得不间断的实时测井数据;(3)合理选择井眼规划方法。首先,结合地表地形,创建一个动态更新的地下地质模型,并规划初始井眼轨迹。随着井的进展,新的测井数据被添加到资产模型中,并进行实时解释。结合实时数据有助于动态更新模型,并能够比较计划和实际偏差调查,以进行航向修正。该程序指导地质导向员更新井计划,进行可行性分析,并在钻井前预测地下不确定性,从而提高储层渗透率和整体油井产能。随钻自动排井是一个相对较新的概念,需要各学科之间的协作。目前,这种技术在非常规资源运营商中越来越重要,因为它提高了井定位的准确性,在降低成本、钻井风险和不确定性的同时提供了更好的产量。此外,当瞄准非常薄、地质复杂的储层时,它可以提供动态变化资产的整体视图。这种方法的使用将使油气运营商能够进行跨领域的协作决策,并简化现有的非常规工作流程。
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Role of Automated and Accurate Well Placement in Reducing Subsurface Complexities and Optimizing Geosteering – An Example from Complex Unconventional Reservoirs
With the increasing demand for hydrocarbons, unconventional reservoirs are gaining prominence and account for a large percentage of oil and gas production. However, these unconventional reservoirs inevitably include challenges that must be carefully managed while planning an extraction strategy to yield maximum recovery. This paper demonstrates the advantages of an integrated and automated well placement workflow to improve geosteering in complex unconventional reservoirs with maximum hydrocarbon recovery. Automated well placement technique is controlled by three primary components: (1) an integrated asset model; (2) availability of uninterrupted, real-time log data; and (3) appropriately selected well planning methods. Initially, a dynamically updatable model of subsurface geology is created that combines surface topography, and an initial well trajectory is planned. As the well progresses, new log data are added to the asset model, and an interpretation is made in real time. Incorporating real-time data helps to dynamically update the model and enable a comparison of planned vs. actual deviation surveys for course corrections. This procedure guides the geosteerer to update well plans, run feasibility analyses, and predict subsurface uncertainties ahead of drilling, thus, increasing the reservoir penetration and overall well productivity. Automated well placement while drilling is a relatively new concept and requires collaboration across various disciplines. Currently, such techniques are gaining importance among operators of unconventional resources as it enhances accuracy in well positioning and provides better production while reducing costs, drilling risks, and uncertainties. In addition, when targeting very thin, geologically complex reservoir layers, it provides a holistic view of the dynamically changing asset. The use of this approach will enable oil and gas operators to make collaborative, cross-domain decisions and streamline existing unconventional workflows.
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