Factors influencing cavity detection in Karst terrain on two-dimensional (2-D) direct current (DC) resistivity survey: A case study from the western part of Thailand

To create a three-dimensional (3-D) cave and cavity network model in Karst terrain from two-dimensional (2-D) direct current resistivity (DCR) profiles, we first need to recognize their effects on the inversion results from a number of special cases. 2-D and 3-D cavity models are created to demonstrate effects from (1) depth of the cavity, (2) size and shape, (3) distance to the edge of the cavity, (4) orientations (inclination and declination) of the cavity and (5) several smaller cavities lying in an array. For other complicated models, combinations of these factors can be used to infer the results. Two parallel DCR profiles from the western part of Thailand were first inverted with the 2-D inversion for interpretation. Knowledge gained from the numerical modeling on these special cases is helpful to constrain the interpretation and also to extend the interpretation to 3-D. This gives us a picture of the 3-D cave and cavity networks beneath the area of study. Two main connected cavities between these two profiles can be inferred from the data along with several local cavities near the surface.

► The depth, size and shape of cavities can greatly influence their detection.
► By ignoring edge effects and orientation, misinterpretations can occur.
► Results from numerical studies can help with obtaining a better interpretation.
► Using only 2D DC resistivity surveys we can construct a 3D interpretation.