Geology topics

Sabodh Garg

Publications and source records attributed to Sabodh Garg.

4 recordsLinked to original sources

USGS2024

Geothermal play fairway analysis, part 1: Example from the Snake River Plain, Idaho

The Snake River Plain (SRP) volcanic province overlies the track of the Yellowstone hotspot, a thermal anomaly that extends deep into the mantle. Most of the area is underlain by a basaltic volcanic province that overlies a mid-crustal intrusive complex, which in turn provides the long-term heat flux needed to sustain geothermal systems. Previous studies have identified several known geothermal resource areas within the SRP. For the geothermal study presented herein, our goals were to: (1) adapt the methodology of Play Fairway Analysis (PFA) for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal PFA model for the SRP and identify the most promising plays, using GIS-based software tools that are standard in the petroleum industry.

Idaho↗

USGS2024

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results.

Geothermics↗

USGS2020

Play fairway analysis in geothermal exploration: The Snake River plain volcanic province

The Snake River volcanic province (SRP) has long been considered a target for geothermal development. It overlies a thermal anomaly that extends deep into the mantle and represents one of the highest heat flow provinces in North America, but systematic exploration been hindered by lack of a conceptual model. Play Fairway Analysis (PFA) is a methodology adapted from the petroleum industry that integrates data at the regional or basin scale to define favorable plays for exploration in a systematic fashion. The success of play fairway analysis in geothermal exploration depends critically on defining a systematic methodology that is grounded in theory and adapted to the geologic and hydrologic framework of real geothermal systems. This study focused on identifying three critical resource parameters for exploitable hydrothermal systems in the Snake River Plain: heat source, reservoir and recharge permeability, and cap or seal. Data included in the compilation for Heat were heat flow, the distribution and ages of volcanic vents, groundwater temperatures, thermal springs and wells, helium isotope anomalies, and reservoir temperatures estimated using geothermometry. Permeability was derived from stress orientations and magnitudes, post-Miocene faults, and subsurface structural lineaments based on magnetic and gravity data. Data for Seal included the distribution of impermeable lake sediments and clay-seal associated with hydrothermal alteration below the regional aquifer. These data were used to compile Common Risk Segment (CRS) maps for Heat, Permeability and Seal, which were combined to create a Composite Common Risk Segment (CCRS) map for all of southern Idaho that reflects the risk associated with geothermal resource exploration and helps to identify favorable resource tracks. Our data suggests that important undiscovered geothermal resources may be located in several areas of the SRP, including the western SRP (associated with buried lineaments capped by lacustrine sediment), at lineament intersections in the central SRP, and along the margins of the eastern SRP. These blind resources are associated with temperatures sufficient to support electricity production, and may be exploitable with existing deep drilling technology. We are testing our methodology by drilling a geothermal test well in Camas Prairie, ID, confirm our predictions of permeability and reservoir temperature.

Idaho↗

USGS2016

GIS methodology for geothermal play fairway analysis: Example from the Snake River Plain volcanic province

Play fairway analysis in geothermal exploration derives from a systematic methodology originally developed within the petroleum industry and is based on a geologic and hydrologic framework of identified geothermal systems. We are tailoring this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region. This project has contributed to the success of this approach by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building automated tools to process results. ArcGIS was used to compile a range of different data types, which we refer to as ‘elements’ (e.g., faults, vents, heatflow…), with distinct characteristics and confidence values. Raw data for each element were transformed into data layers with a common format. Because different data types have different uncertainties, each evidence layer had an accompanying confidence layer, which reflects spatial variations in these uncertainties. Risk maps represent the product of evidence and confidence layers, and are the basic building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map for analysis that reveals favorable areas for geothermal exploration. Python scripts were developed to automate data processing and to enhance the flexibility of the data analysis. Python scripting provided the structure that makes a custom workflow possible. Nearly every tool available in the ArcGIS ArcToolbox can be executed using commands in the Python programming language. This enabled the construction of a group of tools that could automate most of the processing for the project. Currently, our tools are repeatable, scalable, modifiable, and transferrable, allowing us to automate the task of data analysis and the production of CRS and CCRS maps. Our ultimate goal is to produce a toolkit that can be imported into ArcGIS and applied to any geothermal play type, with fully tunable parameters that will allow for the production of multiple versions of the CRS and CCRS maps in order to better test for sensitivity and to validate results.

Idaho↗