Geological data extraction from lidar 3-D photorealistic models: A case study in an organic-rich mudstone, Eagle Ford Formation, Texas

Abstract

The use of lidar (light detection and ranging) 3-D photorealistic outcrop models, combined with traditional sedimentological and structural field data, improves the accuracy and efficiency of qualitative and quantitative characterization of outcrops, which in turn can be used as analogs for reservoir modeling and other geologic purposes. This paper illustrates how geological data extraction from 3-D photorealistic outcrop models can be exploited, and presents some novel workflows that reduce the time needed for postprocessing. The extracted data are calibrated with conventional outcrop studies and allow extensive quantitative analyses and detailed statistical examinations of the distribution, dimension, and shape of geological features that can be used to define and build geological models. We present the first statistical characterization based on lidar of a set of geological outcrops at centimeter resolution (bed scale) over a distance of 45 km (basin scale). These innovative methods of outcrop visualization and characterization are applied to the Eagle Ford Formation, an important unconventional hydrocarbon play in Texas. The Eagle Ford Formation consists of alternating organic-rich mudstone, limestone, and bentonites; mudstones represent the source and reservoir of the hydrocarbons, limestones control the rock’s brittleness, and bentonites provide time lines for dating and correlating sections. The presented analyses provide empirical relationships that can be applied to better understand geologic processess, to build geologic models, and to reduce uncertainties in exploration and development of hydrocarbon systems.