储热评估:根据实地经验的回顾

M. Grant
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引用次数: 12

摘要

摘要地热资源的储热或容量评估非常简单:正在开发的资源是热量。储热计算简单地计算资源中的热量,类似于计算矿体中的矿石量。该方法在资源开采数值模拟中具有一定的理论依据。虽然在任何资源中都存在重要的未知因素,但其中一些可以通过概率方法(特别是蒙特卡罗方法)来覆盖。澳大利亚地热报告规范代表了这种储热评估的一种规范。然而,随着大量地热资源的开发,近几十年来的经验表明,这种方法非常不可靠,通常偏差很大。特别是,过高估计的倾向导致了该方法可信度的降低。引用了一个例子,简单地应用看似简单的规则会产生荒谬的结果。大部分问题在于“采收率”,即实际可以开采的资源的比例,与实际性能比较表明,过去的值在所有情况下都过高,正如澳大利亚代码的当前版本一样。在确定储层体积和“截止温度”的方式上,还有一些通常被忽视的问题。不同的方法意味着不同报告之间的结果不具有可比性。不同的方法也意味着对控制储层枯竭的物理过程的未知假设。蒙特卡罗方法的失败同样是由于在使用概率时未被认识到违反了逻辑一致性。这些问题的净影响是,该方法不是生成粗略资源估计的简单手段,而且它经常生成错误的结果。通常,这样的结果被高估了。蒙特卡罗方法不提供对这些错误的保护。对于平均采收率为10%的热液系统,应采用澳大利亚地热报告规范。使用这个平均值,结果的误差为±70%。对于增强型地热系统(EGS),采收率应该是几个百分点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stored-heat assessments: a review in the light of field experience
Abstract. Stored-heat or volumetric assessments of geothermal resources are appealingly simple: the resource being exploited is heat. A stored-heat calculation simply computes the amount of heat in the resource, similarly to computing the amount of ore in an ore body. The method has theoretical support in numerical simulations of resource production. While there are significant unknowns in any resource, some of these can be covered by probabilistic approaches, notably a Monte Carlo method. The Australian Geothermal Reporting Code represents one specification of such stored-heat assessments. However the experience of recent decades, with the development of significant numbers of geothermal resources, has shown that the method is highly unreliable and usually biased high. The tendency to overestimates, in particular, has led to the reduced credibility of the method. An example is quoted where simple application of the apparently simple rules gives a ridiculous result. Much of the problem lies in the "recovery factor", the proportion of the resource that can actually be exploited, where comparison with actual performance shows past values have been in all cases too high, as is the current version of the Australian code. There are further problems, usually overlooked, in the way that the reservoir volume and "cutoff temperature" are defined. Differing approaches mean that results between different reports are not comparable. The different approaches also imply unrecognised assumptions about the physical processes controlling reservoir depletion. The failure of Monte Carlo methods is similarly due to unrecognised violation of logical consistency in the use of probabilities. The net effect of these problems is that the method is not a simple means to generate a rough resource estimate, and it often generates faulty results. Usually, such results are overestimates. Monte Carlo methods do not provide a protection against these errors. The Australian Geothermal Reporting Code should be used for hydrothermal systems with an average recovery factor of 10%. With this average, results are subject to an error of ±70%. For enhanced geothermal systems (EGS), the recovery factor should be a few percent.
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来源期刊
自引率
0.00%
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0
审稿时长
39 weeks
期刊介绍: Geothermal Energy is a peer-reviewed fully open access journal published under the SpringerOpen brand. It focuses on fundamental and applied research needed to deploy technologies for developing and integrating geothermal energy as one key element in the future energy portfolio. Contributions include geological, geophysical, and geochemical studies; exploration of geothermal fields; reservoir characterization and modeling; development of productivity-enhancing methods; and approaches to achieve robust and economic plant operation. Geothermal Energy serves to examine the interaction of individual system components while taking the whole process into account, from the development of the reservoir to the economic provision of geothermal energy.
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