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Abstract

AAPG Bulletin, V. 102, No. 11 (November 2018), P. 2355-2387.

Copyright ©2018. The American Association of Petroleum Geologists. All rights reserved.

DOI: 10.1306/04251817103

Evaluation of a workflow to derive terrestrial light detection and ranging fracture statistics of a tight gas sandstone reservoir analog

Patrick Wüstefeld,1 Maite de Medeiros,2 Bastian Koehrer,3 Dominik Sibbing,4 Leif Kobbelt,5 and Christoph Hilgers6

1Reservoir-Petrology, Energy and Mineral Resources Group (EMR), RWTH Aachen University, Wüllner Strasse 2, 52062 Aachen, Germany; TTE Reservoir Geology, Karlsruhe Institute of Technology (KIT) Campus Transfer GmbH, Kaiserstrasse 12, 76131 Karlsruhe, Germany; [email protected]
2Chalk Assets, Wintershall Noordzee B.V., Bogaardplein 47, 2284 DP Rijswijk, The Netherlands; [email protected]
3Development Department, Wintershall Norge AS, Laberget 28, 4020 Stavanger, Norway; [email protected]
4Computer Graphics and Multimedia Group, RWTH Aachen University, Ahornstrasse 55, 52074 Aachen, Germany; [email protected]
5Computer Graphics and Multimedia Group, RWTH Aachen University, Ahornstrasse 55, 52074 Aachen, Germany; [email protected]
6TTE Reservoir Geology, KIT Campus Transfer GmbH, Kaiserstrasse 12, 76131 Karlsruhe, Germany; Institute of Applied Geosciences, Structural Geology and Tectonics, KIT, Adenauerring 20a, 76131 Karlsruhe, Germany; [email protected]

ABSTRACT

Understanding natural fracture networks in the subsurface is highly challenging, as direct one-dimensional borehole data are unable to reflect their spatial complexity, and three-dimensional seismic data are limited in spatial resolution to resolve individual meter-scale fractures.

Here, we present a prototype workflow for automated fracture detection along horizontal scan lines using terrestrial light detection and ranging (t-LIDAR). Data are derived from a kilometer-scale Pennsylvanian (locally upper Carboniferous) reservoir outcrop analog in the Lower Saxony Basin, northwestern Germany. The workflow allows the t-LIDAR data to be integrated into conventional reservoir-modeling software for characterizing natural fracture networks with regard to orientation and spatial distribution. The analysis outlines the lateral reorientation of fractures from a west–southwest/east–northeast strike, near a normal fault with approximately 600 m (∼1970 ft) displacement, toward an east–west strike away from the fault. Fracture corridors, 10–20 m (33–66 ft) wide, are present in unfaulted rocks with an average fracture density of 3.4–3.9 m−1 (11.2–12.8 ft−1). A reservoir-scale digital outcrop model was constructed as a basis for data integration. The fracture detection and analysis serve as input for a stochastically modeled discrete fracture network, demonstrating the transferability of the derived data into standard hydrocarbon exploration-and-production-industry approaches.

The presented t-LIDAR workflow provides a powerful tool for quantitative spatial analysis of outcrop analogs, in terms of natural fracture network characterization, and enriches classical outcrop investigation techniques. This study may contribute to a better application of outcrop analog data to naturally fractured reservoirs in the subsurface, reducing uncertainties in the characterization of this reservoir type at depth.

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