基于多因素的油田可采储量不确定性分析

Uncertainty analysis of oilfield recoverable reserves based on multi-factors

油田可采储量通常是通过经验公式法等确定性方法进行预测,所得结果往往是单一值,无法确定风险因素对可采储量计算带来的影响。本文提出采用不确定性分析方法将断层封闭性、原油体积系数、流体黏度、油水相对渗透率、水体大小、井网、油水井表皮系数等影响可采储量的动态因素考虑进来,先通过单因素敏感性分析筛选出主要影响因素,并制定风险消除方案以缩小不确定范围;然后对各动态参数按一定概率分布类型进行蒙特卡洛模拟,所得储量结果呈现为不同发生概率的数值区间,从而实现了可采储量不确定性分析的定量化。西非安哥拉PCG深水油田应用表明,本文方法拓宽了可采储量评价的思路,提高了可采储量预测的可信度,适用于油田开发各阶段,尤其适合数据资料尚不完善、不确定性较大的开发初期,对油藏开发的投资决策及科学管理具有实际意义。

Oilfield recoverable reserves are usually predicted by deterministic methods such as the empirical formula method, the result is often a single value that is unable to determine the effects of risk factors on the recoverable reserves calculation. In this paper, an uncertainty analysis method is proposed by taking some dynamic parameters into consideration, including the fault sealing factor, oil volume factor, fluid viscosity, oil and water relative permeability, aquifer size, well pattern and wellbore skin. Firstly, a single factor sensitivity analysis is performed to screen out main influencing factors, which narrows the scope of uncertainty by making de-risk plan. Secondly, a Monte Carlo simulation is applied to recoverable reserves calculation based on different probability distribution functions of dynamic parameters. The final calculation result shows as a value range of recoverable reserves, and each value corresponds to a probability. Thus, the quantification of uncertainty analysis in recoverable reserves calculation is achieved. Application in Angolan PCG oilfield in West Africa shows that this method broadens the recoverable reserves evaluation methods and improves the credibility of the recoverable reserves prediction, which is applicable to each stage of the oilfield development, especially for the early development stage which is thought to be lack of enough data and to have large uncertainty. This is of importance and practical significance for the investment decision and scientific management of reservoir development.