From Field Fractures to Reservoir Prediction: Utilizing Drones, Virtual Outcrop and Digital Data Analysis to Input Into Discrete Fracture Network (DFN) Models

Abstract

Using outcrop analogues to understand subsurface rock geometries, geological processes, and fault and fracture attributes is of great importance in the petroleum industry. For fractured systems outcrop analogues raise particular challenges including: understanding the difference in timing of fracture systems, mineralization, and the effect of tectonic unloading. The use of fractured analogues is further complicated by limited exposure and/or accessibility of most rock outcrops that restricts full capture of the 3D fracture geometry used to predict the connectivity of a fracture system. Utilizing drone technology, photogrammetry and digital data capture we map and model fracture networks in shale sequences to test the efficacy of these ‘new’ digital approaches for the creation of better reservoir scale DFNs from outcrop data. We present data from potential shale-gas resource field outcrops from the UK and USA, to demonstrate our methodology and the predictability of fractures for the two analogues. Photography for photogrammetry has been captured via drone, photo-pole and conventional techniques to create a layered set of imagery at different scales. At both sites, creek-sections in the USA and coastal bench and cliffs in the UK, the outcrop is only partially accessible. The virtual 3D models, created by photogrammetry, allow a more complete picture of the outcrop and fracture network to be built and interpreted. Interpretation of the 3D models is aided by fieldwork, linear scan lines and mapping. Digital interpretation of the models and subsequent analysis enables fracture attributes to be assessed at a range of scales, using different techniques (e.g. linear and circular scan lines). These traditional field techniques for assessment of fracture attributes can be completed automatically on the digital models, enabling efficient assessment of the efficacy of the techniques. The difference in scale of the digital imagery allows an assessment of up-scaling, an issue for building effective DFNs from outcrop data and predicting reservoir fractures. We assess the up-scaling potential and the effectiveness of 3D model creation and interpretation, over reliance on 2D linear or circular scans and traditional field data collection. Our focus is on assessing the ability to predict and upscale fractures from outcrop analogues to a reservoir scale to create effective DFN predictions for unconventional resources.

AAPG Datapages/Search and Discovery Article #90216 ©2015 AAPG Annual Convention and Exhibition, Denver, CO., May 31 - June 3, 2015