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

Abstract

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 blind geothermal resources through the development of Geothermal Play Fairways. The studied area include 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, but where their extent, risk and exploitability are poorly understood and understudied on both local and regional scales. The studied region is discretized into grid blocks with a size of 2 × 2 km. Two main play fairway elements for geothermal resources 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 due to poor coverage. To applied fuzzy logic for identifying blind geothermal resource, first, a set of fuzzy numbers and rules are formed based on data histogram and expert opinion. Then for each grid block, a fuzzy logic rule is applied to combined different type of data to arrive a favorability map and the uncertainty associated with the map. The final map is able to identify existing geothermal resources and new areas with potential. The proposed methodology is generic and should be applied to other areas.