Representing fractures explicitly using a discrete fracture network (DFN) approach is often necessary to model the complex physics that govern thermo-hydro-mechanical–chemical processes (THMC) in porous media. DFNs find applications in modelling geothermal heat recovery, hydrocarbon exploitation, and groundwater flow. It is advantageous to construct DFNs from the photogrammetry of fractured outcrop analogues as the DFNs would capture realistic, fracture network properties. Recent advances in drone photogrammetry have greatly simplified the process of acquiring outcrop images, and there is a remarkable increase in the volume of image data that can be routinely generated. However, manually digitizing fracture traces is time-consuming and inevitably subject to interpreter bias. Additionally, variations in interpretation style can result in different fracture network geometries, which, may then influence modelling results depending on the use case of the fracture study. In this paper, an automated fracture trace detection technique is introduced. The method consists of ridge detection using the complex shearlet transform coupled with post-processing algorithms that threshold, skeletonize, and vectorize fracture traces. The technique is applied to the task of automatic trace extraction at varying scales of rock discontinuities, ranging from 10⁰ to 10² m. We present automatic trace extraction results from three different fractured outcrop settings. The results indicate that the automated approach enables the extraction of fracture patterns at a volume beyond what is manually feasible. Comparative analysis of automatically extracted results with manual interpretations demonstrates that the method can eliminate the subjectivity that is typically associated with manual interpretation. The proposed method augments the process of characterizing rock fractures from outcrops.

Natural fracture network characteristics can be establishes from high-resolution outcrop images acquired from drone and photogrammetry. Such images might also be good analogues of subsurface naturally fractured reservoirs and can be used to make predictions of the fracture geometry and efficiency at depth. However, even when supplementing fractured reservoir models with outcrop data, gaps will remain in the model and fracture network extrapolation methods are required. In this paper we used fracture networks interpreted from two outcrops from the Apodi area, Brazil, to present a revised and innovative method of fracture network geometry prediction using the multiple-point statistics (MPS) method. The MPS method presented in this article uses a series of small synthetic training images (TIs) representing the geological variability of fracture parameters observed locally in the field. The TIs contain the statistical characteristics of the network (i.e. orientation, spacing, length/height and topology) and allow for the representation of a complex arrangement of fracture networks. These images are flexible, as they can be simply sketched by the user. We proposed to simultaneously use a set of training images in specific elementary zones of the Apodi outcrops in order to best replicate the non-stationarity of the reference network. A sensitivity analysis was conducted to emphasise the influence of the conditioning data, the simulation parameters and the training images used. Fracture density computations were performed on selected realisations and compared to the reference outcrop fracture interpretation to qualitatively evaluate the accuracy of our simulations. The method proposed here is adaptable in terms of training images and probability maps to ensure that the geological complexity in the simulation process is accounted for. It can be used on any type of rock containing natural fractures in any kind of tectonic context. This workflow can also be applied to the subsurface to predict the fracture arrangement and fluid flow efficiency in water, geothermal or hydrocarbon fractured reservoirs.

The 100 000 m² wave-cut pavement in the Bristol Channel near Lilstock, UK, is a world-class outcrop, perfectly exposing a very large fracture network in several thin limestone layers. We present an analysis based on manual interpretation of fracture generations in selected domains and compare it with automated fracture tracing. Our dataset of high-resolution aerial photographs of the complete outcrop was acquired by an unmanned aerial vehicle, using a survey altitude optimized to resolve all fractures. We map fractures and identify fracture generations based on abutting and overprinting criteria, and we present the fracture networks of five selected representative domains. Each domain is also mapped automatically using ridge detection based on the complex shearlet transform method. The automatic fracture detection technique provides results close to the manually traced fracture networks in shorter time but with a bias towards closely spaced Y over X nodes. The assignment of fractures into generations cannot yet be done automatically, because the fracture traces extracted by the automatic method are segmented at the nodes, unlike the manual interpretation in which fractures are traced as a path from fracture tip to fracture tip and consist of several connected segments. This segmentation makes an interpretation of relative age impossible, because the identification of correct abutting relationships requires the investigation of the complete fracture trace by following a clearly defined set of rules. Generations 1 and 2 are long fractures that traverse all domains. Generation 3 is only present in the southwestern domains. Generation 4 follows an ENE–WSW striking trend, is suborthogonal to generations 1 and 2, and abuts on them and generation 3, if present. Generations 5 is the youngest fracture set with a range of orientations, creating polygonal patterns by abutting at all other fracture generations. Our mapping results show that the northeastern domains only contain four fracture generations; thus, the five generations of the outcrop identified in the southwestern domains are either not all present in each of the five domains or vary locally in their geometry, preventing the interpreter from linking the fractures to their respective generation over several spatially separate mapping domains. Fracture intensities differ between domains where the lowest is in the NE with 7.3 m⁻¹ and the highest is in the SW with 10 m⁻¹, coinciding with different fracture orientations and distributions of abutting relationships. Each domain has slightly different fracture network characteristics, and greater connectivity occurs where the development of later shorter fractures is not affected by the stress shadowing of pre-existing longer fractures.

In carbonate rocks, channelized fluid flow through fracture conduits can result in the development of large and connected karst networks. These cavity systems have been found in multiple hydrocarbon and geothermal reservoirs, and are often associated with high-permeability zones, but also pose significant challenges in drilling and reservoir management. Here, we expand on the observed interplay between fractures, fluid flow and large cave systems, using outcrop analysis, drone imagery and fluid-flow modelling. The studied carbonate rocks are heavily fractured and are part of the Salitre Formation (750–650 Ma), located in central Bahia (NE Brazil). Firstly, the fracture and cave network data show a similar geometry, and both systems depict three main orientations, namely; NNE–SSW, NW–SE and ESE–WNW. Moreover, the two datasets are dominated by the longer NNE–SSW features. These observed similarities suggest that the fractures and caves are related. The presented numerical results further acknowledge this observed correlation. These results show that open fractures act as the main fluid-flow conduits, with the aperture model defining the fracture-controlled flow contribution. Furthermore, the performed modelling highlights that geometrical features such as length, orientation and connectivity play an important role in the preferred flow orientations. Thematic collection: This article is part of the Naturally Fractured Reservoirs collection available at: https://www.lyellcollection.org/cc/naturally-fractured-reservoirs

Pore pressure and its relationship with fracture net pressure has been reported qualitatively from both field and experimental observations. From a modeling perspective, the ubiquitously used pseudo 3D (P3D) models that are based on linear elastic fracture mechanics (LEFM) do not include the effect of reservoir depletion (or overpressure). Models that utilize effective stress as propagation criteria with a cohesive zone description, introduce the pore pressure directly into the simulation and hence can potentially capture the effect of pore pressure on fracture propagation. This work investigates the effect of pore pressure on hydraulic fracturing net pressure and geometry using empirical and numerical simulation approaches. We carried out an analysis of more than 400 datafrac injections spanning a wide range of geological ages and depositional environments in order to investigate the relationship between observed net pressure and reservoir pore pressure. The net fracture propagation pressure from the fracture treatment analysis was seen to be correlated with the effective stress in the reservoir. Fracture propagation simulations were performed using a coupled finite element – finite difference fracture simulator. The code uses a cohesive zone model (CZM) to describe fracture propagation. Four different effective stress scenarios were used to study the effect of effective stress on net pressure. The simulation results closely match the empirical relation between net pressure and effective stress as obtained from the analysis of actual frac treatment data. It is observed from the simulations that the magnitude of the effective stress also has an effect on the fracture geometry with a high effective stress leading to wider, shorter and more radial fractures. The derived empirical correlation is hence useful as a fracture design parameter. The datafrac net pressure diagnostics workflow in the pseudo 3D models can incorporate local tip pore pressure as a new pressure matching parameter. The pore pressure effect can thus explain high net pressures routinely observed in frac operations and also as a containment mechanism.