Darajat Geothermal Field Expansion Performance- A Probabilistic Forecast
Darajat Geothermal Field Expansion Performance- A Probabilistic Forecast
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达拉贾特地热田扩张表现——概率预测
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
Jeffrey W. Roberts
中科院分区：
文献类型：
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作者：
V. Hoang;Ontowiryo Alamsyah;Jeffrey W. Roberts
由于所收集数据和评估过程的不确定性，性能预测可能会严重高估或低估地下资源容量。我们应用了一个围绕实验设计方法开发的过程，以捕捉达拉贾特野外静态模型构建、动态模拟模型构建、校准和预测中存在的相关不确定性。这个过程系统地识别、排序和量化影响现场表现的关键参数。它生成了全范围的概率场发电能力分布，可以为经济评估、开发规划和决策制定提供比依赖单一确定性预测更好的平台。储层和地质参数的不确定性排序以及预测的产能分布为油田运营商提供了一个框架，以探索不同的扩张方案，并制定有效的风险管理计划，以减轻潜在的不足。
Performance forecasts can either significantly overestimate or underestimate a subsurface resource capacity due to uncertainties associated with the collected data and the evaluation process. We applied a process developed around the Experiment Design methodology to capture relevant uncertainties existing in the Darajat’s field static model construction, the dynamic simulation model building, calibration, and forecasting. This process systematically identifies, ranks, and quantifies key parameters affecting field performance. It generates a full range of probabilistic field generating capacity distributions that can provide a better platform for the economic evaluations, development planning, and decision making than relying on a single deterministic projection. The ranking of the reservoir and geologic parameters’ uncertainty and the projected performance distribution provide a framework for the field operator to explore different expansion alternatives as well as to develop an effective risk management plan to mitigate the potential shortfalls.