tularosa-basin-play-fairway-analysis-model

The National Renewable Energy Laboratory in the US specializes in the research and development of renewable energy, energy efficiency, energy systems integration, and sustainable transportation.

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National Renewable Energy Laboratory (NREL)

Tularosa Basin weights of evidence play fairway analysis training site points from known geothermal systems and hot springs. The training sites in this dataset were taken from hot springs and know geothermal areas in the Great Basin and New Mexico. These were used in weights of evidence PFA analysis.

Weights of Evidence Training Sites.zip

This is the heat composite risk segment of the Tularosa Basin, New Mexico and Texas -- used for geothermal play fairway analysis. Temperature gradient, quartz geothermometer, and heat flow data were integrated using the Union overlay method. Classification was as follows. Temperature Gradients: 0 degC/km – 60 degC/km = High Risk; 60 degC/km – 80 degC/km = Medium Risk; > 80 degC/km = Low Risk. Quartz Geothermometers: 0 degC – 60 degC = High Risk; 60 degC – 80 degC = Medium Risk; > 80 degC = Low Risk. Heat Flow: 55 – 70 = High Risk; 70 – 85 = Medium Risk; > 85 = Low Risk.

Heat Composite Risk Segment.zip

This is the final deterministic geothermal play fairway analysis model of the Tularosa Basin, New Mexico and Texas. This layer was created by applying Dissolve to the Union overlay version to simplify polygons. Petroleum industry logic was used for this model (Reference: Fraser, et al., 2001).

Deterministic PFA Dissolve.zip

This is the final deterministic certainty layer for Tularosa Basin deterministic play fairway analysis. Certainty was based upon the presence, spatial correlation, and agreement of heat composite risk segments.

Deterministic Certainty.zip

This is a deterministic geothermal play fairway analysis model of the Tularosa Basin, New Mexico and Texas. It was created using petroleum industry logic (see paper referenced below). Composite risk segment (CRS) maps representing heat, fracture permeability, and ground water were fused using the Union Overlay method. Polygons were then classified as low, medium, or high risk based upon input CRS values (Fraser et al., 2001).