Abstract This paper presents a workflow for resource characterization and assessment of exploration geothermal fields with minimum data. Our approach utilizes stochastic methods to estimate the temperature distribution at potential target depths by focusing on the impact of uncertain input parameters such as thermal conductivity and porosity. We first perform stochastic forward simulations to determine the initial steady-state thermal field and subsequently quantify the uncertainty via a Monte Carlo approach known as Sequential Gaussian Simulation (SGSim). Next, we analyze the in-field likelihood of success for Enhanced Geothermal Systems by simulating hypothetical energy production scenarios based on existing geothermal installations. This approach is applied to the case study of a Hot Dry Rock geothermal field with two exploration wells, located in Acoculco, Mexico. Data scarcity in this field necessitates the use of stochastic methods for plausible prediction of reservoir temperature used to determine the accessible thermal power. Once reliable temperature estimates are obtained at potential target depths, we simulate production scenarios by assuming a prior successful stimulation process in the existing wells. In addition to providing preliminary estimates of thermal power for different injection/production rates, stimulated volumes and created permeability, we present the long-term impact of production on the temperature and pressure fields.

中文翻译：

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用于评估具有稀疏数据的地热绿地中增强型地热系统 (EGS) 潜力的随机工作流程：墨西哥 Acoculco 的案例研究

摘要 本文提出了一种利用最少数据对勘探地热田进行资源表征和评估的工作流程。我们的方法通过关注热导率和孔隙率等不确定输入参数的影响，利用随机方法来估计潜在目标深度的温度分布。我们首先执行随机正向模拟以确定初始稳态热场，然后通过称为序列高斯模拟 (SGSim) 的蒙特卡罗方法量化不确定性。接下来，我们通过模拟基于现有地热装置的假设能源生产场景来分析增强型地热系统的现场成功可能性。该方法应用于具有两个勘探井的干热岩地热田的案例研究，位于墨西哥阿科库尔科。该领域的数据稀缺需要使用随机方法对用于确定可用热功率的储层温度进行合理预测。一旦在潜在目标深度获得可靠的温度估计，我们就通过假设现有井中先前成功的增产过程来模拟生产场景。除了提供不同注入/生产速率、增产体积和产生的渗透率的热功率的初步估计外，我们还介绍了生产对温度和压力场的长期影响。一旦在潜在目标深度获得可靠的温度估计，我们就通过假设现有井中先前成功的增产过程来模拟生产场景。除了提供不同注入/生产速率、增产体积和产生的渗透率的热功率的初步估计外，我们还介绍了生产对温度和压力场的长期影响。一旦在潜在目标深度获得可靠的温度估计，我们就通过假设现有井中先前成功的增产过程来模拟生产场景。除了提供不同注入/生产速率、增产体积和产生的渗透率的热功率的初步估计外，我们还介绍了生产对温度和压力场的长期影响。