Constructing the Apparent Geological Model by Fusing Surface Resistivity Survey and Borehole Records

Area of Science:

• Geophysics
• Hydrogeology
• Geology

Background:

• Surface resistivity surveys and wellbore logs are crucial for geological subsurface characterization.
• Integrating diverse geophysical and geological datasets can improve subsurface model accuracy.
• Accurate geological models are essential for effective groundwater resource management and simulations.

Purpose of the Study:

• To develop and validate a data fusion approach for constructing an apparent geological model.
• To integrate surface electrical resistivity measurements with wellbore log data.
• To enhance the spatial accuracy and detail of geological models for groundwater studies.

Main Methods:

• Data fusion of dense electrical resistivity measurements (Schlumberger arrays) and wellbore logs.
• Application of an optimization algorithm and geostatistic interpolation (inverse distance method).
• Utilized a non-parametric bootstrap method for uncertainty analysis of predicted sediment types.

Main Results:

• Generated an apparent formation factor model from surface resistivity and groundwater resistivity.
• Converted the formation factor model into a detailed apparent geological model using optimized criteria.
• Achieved predictive uncertainties for clay, gravel, and sand below 5%.

Conclusions:

• The developed data fusion approach successfully captures spatial features of sediment types.
• The model can be self-updated with new data, allowing for continuous refinement.
• The enhanced geological model provides valuable input for groundwater simulations and multidisciplinary studies.