Construction of Discrete Fracture Networks based on data from 3D geological reconstructions of outcrops.
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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.
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The Lilstock outcrop in the southern Bristol Channel provides exceptional exposures of several limestone beds displaying stratabound fracture networks, providing the opportunity to create a very large, complete, and ground-truthed fracture model. Here we present the result of automated fracture extraction of high-resolution photogrammetric images (0.9 cm/pixel) of the full outcrop, obtained using an unmanned aerial vehicle, to obtain a spatially extensive, full-resolution map of the complete fracture network with nearly 350,000 ground-truthed fractures. We developed graph-based functions to resolve some common issues that arise in automatic fracture tracing such as incomplete traces, incorrect topology, artificial fragmentation, and linking of fracture segments to generate geologically significant trace interpretations. The fracture networks corresponding to different regions within the outcrop are compared using several network metrics and the results indicate both inter- and intra-network (layer to layer) structural variabilities. The dataset is a valuable benchmark in the study of large-scale natural fracture networks and its extension to stochastic network generation in geomodelling. The dataset also highlights the intrinsic spatial variation in natural fracture networks that can occur even in weakly-deformed rocks over relatively short length scales of tens of metres.
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For a long time,the study of 3D geological modeling relies on using exploration data from drill holes or geologic sections.But,on the premise of the lack of large area general geological background modeling,only considering of local region refined modeling often lead to overgeneralization and over-reliance on the data.Plane geological map,which integrates geological field survey and the results of the work with geological expert knowledge,reveals rock stratigraphy and geological structure of the region,is the available and the most direct data source for 3D geological modeling.On the premise of the lack of other geological data,using planar geological map to build 3D geological model is an effective solution.The 3D geological modeling directly based on planar geological map,but it is weak in controllability and the building quality of the geological models is unsatisfactory.To solve this problem,this article proposed a new 3D geological modeling method based on geological plane maps and used cutting profile as the intermediary.The method encrypted the existing data of the study area indirectly,processed complex structures such as folds using cubic spline fitting combining with artificial revision,and realized the automatic drawing of cutting profile based on the geological plane maps.We took regular voxels as the 3D spatial data model,got a series of parallel cutting profile of the study area automatically drawn,and built a rasterized 3D geological model.With Xinggang area,Chongqing City as the study area,the prototype experiment system was built and we verified the effectiveness and practicality.Results showed that the 3D geological modeling method based on geological plane maps is an effective solution to build regional 3D geological model under the condition of lacking of other geological data.
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Carbonates represent major hydrocarbon reservoirs, but often exhibit highly heterogeneous reservoir properties. Outcrop analogues provide important insights into how parameters such as porosity, permeability and natural fractures vary. As such, outcrops can bridge the scale gap between spatially extensive but poor-resolution seismic data and 1D high-resolution well data. However, traditional geological fieldwork typically gathers insufficient data to construct robust geological models. In this study, we have specifically set out to gather key data sets that enable the construction of a geology-driven model. We illustrate this workflow using the exceptionally well-exposed carbonate-dominated outcrops of the Kapp Starostin Formation in central Spitsbergen, Arctic Norway. We fully utilize emerging technologies, notably geo-referenced digital outcrop models (DOMs), to be able to gather quantitative sedimentological-structural data from otherwise inaccessible cliffs. DOMs generated from digital photos are used directly for automatic and manual mapping of fractures. The digital data are complemented with traditional fieldwork (sedimentological logging, scanlines, structural characterization) in order to strengthen the dataset. The geo-modelling involves traditional facies and petrophysical modelling of the 12 identified facies, along with outcrop-based discrete fracture modelling. Finally, the static geo-model is upscaled, and its applications are discussed. The presented workflow uses carbonate outcrops of the Kapp Starostin Formation as input but is highly applicable for other studies where outcrops can be utilized as direct input to constrain a geological model.
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The geological work during stage 2.2 has involved the development of deterministic models for rock domains (RFM) and deformation zones (ZFM), the identification and deterministic modelling of fracture domains (FFM) inside the candidate volume, i.e. the parts of rock domains that are not affected by deformation zones, and the development of statistical models for fractures and minor deformation zones (geological discrete fracture network modelling or geological DFN modelling). The geological DFN model addresses brittle structures at a scale of less than 1 km, which is the lower cut-off in the deterministic modelling of deformation zones. In order to take account of variability in data resolution, deterministic models for rock domains and deformation zones are presented in both regional and local model volumes, while the geological DFN model is valid within specific fracture domains inside the north-western part of the candidate volume, including the target volume. The geological modelling work has evaluated and made use of: A revised bedrock geological map at the ground surface. Geological and geophysical data from 21 cored boreholes and 33 percussion boreholes. Detailed mapping of fractures and rock units along nine excavations or large surface outcrops. Data bearing on the characterisation (including kinematics) of deformation zones. Complementary geochronological and other rock and fracture analytical data. Lineaments identified on the basis of airborne and high-resolution ground magnetic data. A reprocessing of both surface and borehole reflection seismic data. Seismic refraction data. The outputs of the deterministic modelling work are geometric models in RVS format and detailed property tables for rock domains and deformation zones, and a description of fracture domains. The outputs of the geological DFN modelling process are recommended parameters or statistical distributions that describe fracture set orientations, radius sizes, volumetric intensities, spatial correlations and models, and other parameters (lithology and scaling corrections, termination matrices) that are necessary to build stochastic models. Primarily due to the establishment of additional fixed point intersections for rock domain boundaries at depth, adjustments have been made to earlier regional and local rock domain models. These adjustments are only minor in character. Compared with the earlier stage 2.1 model, adjustments in the regional deformation zone model are also, in general, highly limited in character. More important differences, which also affect the local model for deformation zones, concern zones ZFMA2, ZFMF1 and ZFMA8 in the gently dipping set. Significant changes in the modelling of deformation zones also concern the steeply dipping zones with surface trace lengths between 1 and 3 km in the local model volume. A totally revised geological DFN model is presented compared with the latest model (version 1.2). In particular, conceptually distinct alternatives are presented for fracture size modelling.
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Abstract. The stochastic generation of discrete fracture networks (DFN) is a method for modelling fracture patterns used to assess the in situ fragmentation in a volume of rock. The DFN modelling approach is based on the assumption that the natural fragmentation of rocks is a function of the length and connectivity of the fractures within the considered volume of rock. Thus, in order to generate a site-specific DFN, the primary geometric properties of the fracture surfaces within the rock volume (especially orientation, size and fracture intensity as well as the local spatial variability) must be defined as distribution functions (Elmo et al., 2014). The required base statistics are usually obtained from fracture analysis on boreholes, exposed rock surfaces or (to a limited extent) 3D seismics (e.g. Bisdom et al., 2014; Bemis et al., 2014). We adopted a terrestrial close-range photogrammetry approach to capture several outcrops and analyse fracture traces on the exposed rock surfaces, the chosen workflow is based around the use of free and open-source software. Images were acquired from several quarries in the Weschnitzpluton, a granodioritic to quartz monzodioritic pluton in the Bergstrasse Odenwald (e.g. Altherr et al., 1999) using a consumer-grade Nikon D5300 DSLR with fixed focal length instead of a drone or Lidar-system for legal reasons, partially tree-lined outcrops and cost efficiency. Since point clouds obtained from photogrammetry are inherently dimensionless, we used a spherical target with compass and bubble level for scale and proper spatial orientation (Froideval et al., 2019). The exact geolocation is not particularly important for the task, so the use of GPS, total station or georeferenced ground control points is not necessary. Dense point clouds were computed using the open source SfM photogrammetry suite Meshroom (AliceVision, 2021), which can be used for manual or semi-automatic detection of fracture surfaces and their orientation (Schnabel et al., 2007) and to generate orthorectified images of the rock surface to trace fracture lengths and nodes in a GIS (Nyberg et al., 2018). Our investigations proved terrestrial photogrammetry to be a valuable and easily accessible tool in the documentation of natural fracture patterns and a robust base for the generation of DFN networks.
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Current methods for constructing a 3D geological model of an area require field drilling or measured section data which are often not available over large areas. 2D geological maps not only contain information on the distribution of geological strata but also provide sufficient geometric, topological and semantic information for 3D geological modelling. This paper presents a method for constructing a detail 3D model from 2D geological maps. First, a series of parallel cross sections is automatically created from the 2D geological map and the corresponding relationships of the geological objects in the cross sections are recorded. Second, a contour algorithm is used to connect these cross sections to establish a 3D geological model of the study area. The spacing of cross sections has strong impact on the result, we proposed a rule to determine the spacing of cross sections adaptively. As a case study, the method was applied to construct a 3D geological model for Xing-gang area in Chongqing city. The results of this case study suggest that the method is effective to construct a quality 3D geological model solely based on the information from a 2D geological map of the area.
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