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首页> 外文期刊>Energy sources. Part B, Economics,planning,and policy >Monte Carlo Simulation of Oil Fields
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Monte Carlo Simulation of Oil Fields

机译：油田的蒙特卡洛模拟

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摘要

Most investments in the oil and gas industry involve considerable risk with a wide range of potential outcomes for a particular project. However, many economic evaluations are based on the "most likely" results of variables that could be expected without sufficient consideration given to other possible outcomes, and it is well known that initial estimates of all these variables have uncertainty. The data is usually obtained during drilling of the initial oil well, and the sources are geophysical (seismic surveys) for formation depths and the areal extent of the reservoir trap, well logs for formation tops and bottoms, formation porosity, water saturation and possible permeable strata, core analysis for porosity and saturation data, and others. The question is how certain are the values of these variables and what is the probability of these values to occur in the reservoir to evaluate the possible risks? One of the most highly appreciable applications of the risk assessment is the estimation of volumetric reserves of hydrocarbon reservoirs (Monte Carlo). In this study, predictions were made about how statistical distribution and descriptive statistics of porosity, thickness, area, water saturation, recovery factor, and oil formation volume factor affect the simulated original oil in place values of two different oil fields in Turkey, and the results are discussed.
机译：石油和天然气行业中的大多数投资都涉及相当大的风险，并且对特定项目具有广泛的潜在结果。但是，许多经济评估都是基于在没有充分考虑其他可能结果的情况下可以预期的变量的“最可能”结果，并且众所周知，所有这些变量的初始估计都具有不确定性。通常在初始油井钻探期间获得数据，其来源为地层深度和储层圈闭面积的地球物理（地震勘测），地层顶部和底部的测井曲线，地层孔隙度，水饱和度和可能的渗透性。地层，孔隙度和饱和度数据的岩心分析等。问题是这些变量的值如何确定，这些值出现在水库中以评估可能的风险的概率是多少？风险评估最重要的应用之一是碳氢化合物储层体积储量的估算（蒙特卡洛）。在这项研究中，对孔隙度，厚度，面积，水饱和度，采收率和油层形成体积因数的统计分布和描述性统计如何影响土耳其两个不同油田的模拟原始油位值进行了预测，并且结果进行了讨论。

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