Characterization of Fault-Related Dolomite Bodies in Carbonate Reservoirs Using Lidar Scanning
Juliette Lamarche, Jean Borgomano, Bruno Caline, Franck Gisquet, Sylvain Rigaud, Stefan Schröder, Sophie Viseur, 2011. "Characterization of Fault-Related Dolomite Bodies in Carbonate Reservoirs Using Lidar Scanning", Outcrops Revitalized: Tools, Techniques and Applications, Ole J. Martinsen, Andrew J. Pulham, Peter D.W. Haughton, Morgan D. Sullivan
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Fault-related dolomite subsurface reservoirs are formed from fluid circulation that results in significant transformation of the reservoir properties. The geometry and internal organization of such dolomitic reservoirs remain difficult to image with seismics alone. A multi-scale approach is essential to understand and predict the diagenetic processes that control the exact 3D morphology of the dolomite with spatial precision and true dimensions, and consequently the reservoir properties. In this context, we propose an analytical workflow including field work, LIDAR scanning and numerical geology applied to dolomite outcrops in Mesozoic carbonates (SE France). The exposed dolomite-limestone contact exhibits sinuous, irregular and convolute shapes, which are either fault-parallel, bedding-parallel or chaotic. To characterize this complex distribution, we performed LIDAR scanning on 500 m x 150 m cliffs and road cuts with 4.5 cm to 1–1.5 cm average point spacing. The cloud is composed of 22 millions points comprising X, Y, Z, intensity, red, green, and blue attributes. Digitization of the limestone-dolomite boundary was performed in RiscanPro and GOCAD environments, for extracting the true 3D geometry of the dolomite body for further geostatistical and 3D facies modelling. This approach captures the large-scale geometry of the dolomite bodies. However, single RGB or intensity properties do not unequivocally reproduce small-scale (below ∼ 1 m) heterogeneities of the late diagenetic dolomite. Color changes induced by weathering or climatic conditions are of the same size range as the small-scale heterogeneities, thus they are not unique to allow automated tracking on the point set. As a result, the workflow remains time-consuming, and further work is needed to allow calibration of the LIDAR data points with mineralogy.