EAGE Workshop on Naturally Fractured Rocks (NFR)

Modelling Discrete Fracture Networks (DFN) in naturally fractured reservoir (NFR) implies identifying and understanding the fracture spatial distribution and relationships to stratigraphic interfaces (crosscutting or abutment) in 3D. However, capturing fracture geometric parameters in the subsurface has always been a challenging task. To palliate the lack of data, and to better constrain modelling inputs, outcrop analogs are often used. Cooke and Underwood (2001) have shown that bed/inter-bed thickness ratio and mechanical contrasts at bed interfaces are essential to control fracture abutment. Our goal is to predict fracture network geometry in stratified sedimentary rocks. To this purpose, we present a new original python script. We performed an integrated approach that quantifies and automatically computes the bed interface’s compliance to let fractures go through (or not). Accounting for abutment, cross-cutting relations and bed thickness data, a compliance value is calculated for each interface. The process comprises (1) a field survey and (2) the processing of the fracture data. First, we applied the method to a synthetic case study to check the feasibility of the code. Second, we applied the method to naturally fractured and stratified carbonates located in SE France.

In summary, existing methods of using conventional core and logs to deduce porosity appear to severely underestimate secondary porosity development in carbonates. In addition to paleo-current analysis in clastics, fracture characterization and in situ stress determination, borehole images can be used to deduce secondary porosity development by combining with enlarged calipers, partial or complete losses and other engineering data. We have shown the role of diagenesis having either constructive or destructive impact depending on the scenarios. Quantifying dissolution features in subsurface reduces uncertainty. Borehole images can be complemented with 3D seismic to infer the extent of these geo-bodies laterally and vertically.

Linear Elastic Fracture Mechanics allows rapid modelling of fracture propagation, but is only valid in a homogeneous medium so cannot model fractures propagating across mechanical boundaries. We use phase field models to derive empirical expressions for the energy release rate of a fracture crossing a mechanical boundary, as a function of fracture length, layer thickness and the mechanical properties on both sides of the boundary. This is shown to be a combination of the classical LEFM formula but with Young’s Modulus averaged along the length of the fracture, and an additional term for the boundary effect. This boundary term is negligible away from the boundary, but tends to zero or infinity close to the boundary. This expression can be used to simulate fractures propagating across layer boundaries in mechanically layered rocks.

To delve into the connectivity and heterogeneity among different fracture reservoirs, we’ve established a fracture model database rooted in fracture network parameters, notably fracture intensity (P21) as delineated by DMatlas ( Li et al., 2019 ). These models encompass the full range depicted within the ternary diagram of fracture nodes. Each model is subjected to an inverted 5-point well pattern implementation. Employing flow diagnostics techniques, we calculate Time of Flight (TOF) and Lorenz coefficients to measure the well connectivity and heterogeneity of fractured reservoirs, while considering diverse node type patterns and fracture intensities (P21). This methodology empowers us to gauge the impact of fracture patterns and intensity on well connectivity and reservoir heterogeneity. The flow dynamics within fractured reservoirs are markedly shaped by fracture node types and intensity. Utilizing the flow diagnostic approach, fractured reservoir heterogeneity and well connectivity are systematically assessed through the generation of fracture models from a 2D template rooted in graph theory.

Jebel Madar (Adam Foothills, North Oman) is a unique outcrop exposing mid-Cretaceous formation. It is interpreted as a salt-cored, faulted anticline caused by the movement of the Precambrian-Cambrian Ara salt Fm, during the orogeny of the Oman mountains. The exposed rock section covers the Natih down to the Lekhwair formations and, thus, includes the Shuaiba and Kharaib. The Jebel Madar outcrop in its entirety serves as a field-scale analogue for hydrocarbon-producing reservoirs not only across Oman but also the UAE ad Saudi Arabia. Further, the maximum burial depth is comparable to that observed in subsurface fields, thus, making Jebel Madar an ideal study area for fracture- and fault-dominated reservoirs above salt domes under subsurface conditions. Previous researchers have primarily focused on the peripheral regions of Jebel Madar. Fracture patterns in these areas have been described as radial and seemingly independent of regional fault and fracture networks, suggesting a possible influence of salt doming. This project targets the Jebel’s central areas utilizing high-resolution drone photogrammetry with the aim to update and refine the understanding of fault patterns and its structural evolution and provide a comprehensive dataset for virtual reality field trips.

Salt halokinesis and salt dome widely developed in the southwest of the Arabian Gulf and three major tectonic events imprint multiple sets of fracture on the drape fold above salt dome and showcase complex and diverse fracture system in the Upper Jurassic. The objective of this study is to investigate the fracture development under multi-phase deformation and characterize the complex fracture system of the Upper Jurassic in the salt dome dominated area.

In this study, a cause-oriented workflow is proposed to investigate multi-phase fracturing and faulting and characterize the fracture system in salt dome area. Firstly, the conceptual fracture model is established based on the analysis of the regional structural evolution and guides to identify structural evolution locally and characterize multi-scale fracture using multiple seismic attributes. Secondly imaging log is employed to recognize small-scale fracture. Lastly, the recognized fractures are verified by dynamic data and then geologically analysed guided by the conceptual fracture model.

This study shed a light on the fracture evolution and the overprinted fracture system in the salt dome area and provide an insight into the characterization of the distinct fracture in tight carbonate reservoir.

The geometry of fractures, their associated minerology, and the relationships between fracture sets are key controls on subsurface permeabilities in otherwise impermeable rock, and subsequently so too on abstraction of subsurface geo-fluids and heat. Mississippian carbonate rocks represent over 50% of the subcrop geology in Ireland. The succession reveals a transition from transgressive ramp-dominant carbonates gradually developing into a rift basin. Several potential fractured or palaeo-karstified reservoirs exist in the succession, with clean shallow-water carbonate successions near basin-bounding faults at several kilometers depth forming particularly attractive targets.

Most previous work on fractured Irish Mississippian carbonates has focused on qualitatively describing the various fracture sets and their interactions with stratigraphy, with little work done to quantify fracture properties and interactions with varying lithology at scale. This study aims to bridge this gap by supplying quantitative analysis of the interplay between various fracture generations and Irish Mississippian carbonate stratigraphy, employing traditional field techniques such as scan lines with semi-automated fracture picking on digital outcrop models derived from drone photogrammetry.

Our findings on population statistics for different fracture sets will allow assessment of the distribution of discontinuities within discrete fracture models to better predict permeability anisotropy in the subsurface, derisking geothermal well design.

For the last two decades there has been increasing interest for exploring altered and naturally fractured basement rocks underlying the Norwegian Sea. Authors have carried out outcrop and core analyses showing that these altered basement rocks could generally be subdivided into five different facies, controlled by natural fracture types, orientation, cementation, aperture, and degree of physio-chemical alteration. The main interpretation challenges of these basement rocks during drilling are facies variations over short distances, uncertainty related to natural fracture attributes and productivity. The main purpose of the present work is to present an integrated workflow using advanced logging-while-drilling (LWD) data and surface data interpretations to understand and define the basement facies architecture for facilitating future well-placement decisions. By using 3D advance seismic attributes, 2D and 3D ultra-deep azimuthal resistivity (UDAR), conventional log data and X-ray Fluorescence (XRF) elemental cross-plots diagram for igneous rocks based on the relationship between SiO2 vs Na2O+K2O) three main basement units were observed. However, by integrating image interpretation and Nuclear magnetic resonance (NMR) data, the basement was further subdivided into different facies types. Interpreted fractures with their attributes were compared with seismic attributes, and stochastic fracture network analysis was carried out.

We introduce a novel method of representing and comparing fracture networks across scales that incorporates geometry and topology of fracture patterns. The Minkowski Fingerprint is a unique representation of a fracture network built on the spatial graph abstraction of fracturing where fracture intersections form graph nodes and connecting segments form edges. The partitioning of space within the edge connections in such a spatial graph can be represented as sets of connected tessellations to which morphometric analysis is applied. In particular, we use Minkowski tensor-based morphometric quantification to the tessellations, deriving multi-scale probability distributions and forming a unique fingerprint of any fracture network. We derive a similarity metric known as the Minkowski Fingerprint Distance that can compare a pair of networks. The MFD is then used to quantify variations in large-scale fracture patterns using hierarchical clustering. Examples of such intra-network and inter-network fracturing variations are showcased from limestone outcrops of the Franconian Alb.

A new methodology and workflow are presented for the 3D interpretation and modelling of datasets such as 3D scans on geological outcrops, caves and mines. The unique workflow permits to integrate the results of data analyses and geologic knowledge obtained, to generate a full 3D geological model, and to simulate a data-driven 3D model of the fault and fracture network which fully comprises the on-site observations. An example is presented where the workflow is applied to an outcrop of a stratified, fractured and faulted limestone. Implications will be highlighted for ongoing applications in mining, and subsurface modelling for geofluid exploitation, extraction, and storage (e.g., Oil and Gas, CCUS, H2, Geothermal Energy).