Using Fuzzy Logic to Identify Geothermal Resources and Quantify Exploration Risk through Play Fairway Analysis

摘要

The objective of this work is to develop a methodology based on fuzzy logic to address the overarching theme of uncertainty quantification and reduction in identifying geothermal resources through Geothermal Play Fairway analysis. The study area includes regions from northeastern California, southern Oregon, and northwestern Nevada, bounded on the east by the Basin and Range extensional regime, and on the west by the Cascade (volcanic) Range. This is a region where geothermal resources are known to exist based on past exploration efforts, but their extent, risk and exploitability are poorly understood and understudied on both local and regional scales. Two main geothermal resource elements are investigated: permeability and heat. The available data used to explain these two elements are structural data (including fault length, age, stress, strain and seismicity) and heat source related measurements (including maximum heat flow data, maximum temperature data, maximum downhole temperature, smoothed heat flow, and geothermometry measurements). Fluid geochemistry data and some geophysical measurements (e.g., magnetotellurics data) are investigated, but not included in the assessment due to limited regional coverage. To apply fuzzy logic for identifying blind geothermal resources, first, a set of fuzzy numbers and rules are formed based on data histograms and expert opinion. Then for each grid block (the study region was discretized into grid blocks with a size of 2 × 2 km), a fuzzy logic rule is applied to combine different data types to arrive at a favorability map and the uncertainty associated with the map. The final map is able to identify known geothermal resources and new areas with potential. The proposed methodology is generic and can be applied to other areas.