3D Model of a geothermal area with cross sections of 3D seismic and density profile along a proposed EGS well pair. The EGS wells were planned going through microseismic from a previous stimulation study. Surface microgravity data and temperature logs from offset wells are also shown.
The geothermal exploration method often involves an analysis of data related to various surface and subsurface geoscientific properties. Geoscientific professionals and engineers use different evaluation methods to derive a conclusion on the feasibility of the potential geothermal project. The technology that allows efficient integration and visualization of geothermal exploration data can act as an effective tool to reduce uncertainty as well as potential production capability of the geothermal reservoir.
4D visualization is one such methodology that can aid the geothermal exploration phase with proper integration and modeling of the associated data. This simplifies the process of comparative analysis of diverse data. Based on this analysis, asset teams can make informed and efficient decisions in relation to project development and economic investment.
Data Integration for Geothermal Exploration Method
An effective geothermal exploration method should provide a complete overview of the surface and subsurface parameters and define associated risks and uncertainties regarding reservoir characterization. Asset teams can achieve this information through regional and local scale exploration which characterizes data within a defined geospatial limit. The data can be captured through various methods including seismic surveys, gravity and magnetic studies, remote sensing, and logging processes. Availability of data from existing geothermal projects can also help in establishing a strong background for well-defined exploration analysis.
Efficient integration of the data collected through various exploration techniques facilitates proper analysis and correlation development between these multidimensional parameters. The parameters may include temperature, porosity and permeability, thermal conductivity, and resistivity which gives insight into the potential geothermal reserve. These parameters can further be integrated with topographical and terrain data including existing infrastructures, roads, and power lines. As these data are stored in different formats, it requires a substantial effort from engineers and geoscientists to combine and give an efficient interpretation of the prospective geothermal localities. This process can be considerably simplified using data integration and visualization platforms for developing a conceptual model.
Analyzing Geothermal Data With 4D Visualization
The comprehensive visualization of all the exploration data and models in a single geospatial framework assists the decision-making process during the exploration phase. A three-dimensional model usually provides insight into geoscientific and thermodynamic properties in the reservoir. With the addition of temporal data, parameters such as heat flow, surface microgravity, micro-seismic events along the reservoir can be monitored with time. Additionally, a 4D geospatial model allows asset teams to:
- Develop correlation from known geothermal data and models
- Visualize the temperature data on a local and regional scale through the integration of multiple well data along with regional maps
- Forecast future geothermal productivity of the reservoir using time-lapse data
- Define heat and fluid flow in a geothermal reserve over time
- Analyze and reduce uncertainties regarding geothermal “pay zone” and associated productivity
- Define subsurface lithology for geothermal well planning
- Reduce risk in geothermal project development
CoViz 4D: Enhanced Analysis With 4D Visualization
Geothermal exploration projects can greatly benefit from the four-dimensional visualization ability of CoViz 4D. The geological data and model obtained during the exploration phase through logging and geoscientific surveys can be integrated with the pre-existing geophysical data using CoViz 4D to create a detailed conceptual model.
The visualization of these data helps engineers identify the gap in the information or uncertainties in the exploration phase. Adding a time-phased value to these data parameters assist in estimating the future performance of the reservoir. Based on this estimation, engineers, geoscientists, and investors can make an informed decision about the economic worth of the project.