Integrated Fractured Reservoir Characterization: A Case Study in a North Africa Field

Abstract

In fractured reservoirs, data directly related to fractures are scarce and uni-dimensional (i.e. cores and image logs). Other types of data are better distributed and have proved to be related to fracturing but only indirectly (e.g. lithology or large scale structure). In such reservoirs, however, one has to understand fracture distribution and behavior at the field scale. A methodology has been developed within TotalFinaElf to define the relationships of all sources of data to fracturing and to integrate them and compared to another independent published method. To that end, a systematic work flow which goes from 1D to 2D and from static to dynamic data has been defined and various technologies tested. A field case in North Africa is taken to illustrate this methodology. In this field, fracture data from image logs have been related to: production data; 3D seismic attributes (coherency, amplitude, structural curvature) and fault interpretation and strain; log data such as porosity, thickness and lithology index. The former type of data is used to understand the contribution of each fracture set to flow. The latter two types of data are used to better map fracture distribution at the field scale. Ultimately, this mapping is calibrated with the production data of the other wells where fracturing data are not available and is then used to validate the specific role of fracturing in this field. A better reservoir simulation and infill well planning can be subsequently achieved. Introduction Fractured reservoirs are by nature highly heterogeneous. In such reservoirs, fracture systems control permeability and can also control porosity. Fracture modeling is therefore a key development issue and requires an integrated approach from geology to reservoir simulation and well planning. The geometry (i.e. static model) of the fracture network is generally defined from well data (i.e. cores or image logs) using conventional structural geology techniques. Then, fracture permeability can be assessed by relating the fracture aperture to the fracture excess conductivity measured on electrical image logs1 and/or to critically stressed fractures within the present day stress field2. However, it is the authors' opinion that such approaches can only give, in the best case, a relative estimate of the fracture permeability. A quantitative modeling of fracture flow behavior is therefore required (i.e. dynamic model). At the well scale, this can be done by constructing Discrete Fracture Networks (DFN)3–4 through which flow is modeled and which are matched to well test data5. Ultimately, these models can help in determining the fracture parameters required in dual porosity / dual permeability reservoir flow simulation6,7. However, if these DFN models are appropriate for reservoir sector models, their application to full field simulation is somewhat difficult since their extrapolation outside the well scale can be limited by the heterogeneous vertical and lateral distribution of the fracture networks. The modeling of the spatial distribution of fracturing at the scale of the entire field and its calibration to well data is the purpose of this paper.

Structurally complex reservoirs: an introduction

“…The process of populating and upscaling a fracture model is conceptually similar to that for a matrix model but generally more difficult and less advanced. Techniques include simple interpolation between wells through conventional geostatistical techniques such as kriging (Olarewaju et al 1997), neural networks (Ouenes & Hartley 2000) and methods which simultaneously incorporate static and dynamic data (Gauthier et al 2002). Much modern effort is devoted to the construction and analysis of a discrete fracture network (DFN) model, in which a stochastically or (rarely) deterministically generated set of fractures is populated into a map or a 3D volume.…”

Simulated annealing technique in discrete fracture network inversion: optimizing the optimization

“…Several authors have used SA to model reservoir fractures with certain success [3,4,7,10,13,15,20]. They attempt to evaluate spatial distribution of fracture intensity (or similar indexes that define fracture presence).…”

The NERC Micro to Macro Programme: implications for fluid resource management

“…An exception to this might be a fracture set that was formed under a palaeo-stress state shortly before, or contemporaneously with, hydrocarbon fill, which inhibited fracture healing when the stress state altered to its modern-day configuration (e.g. Stowell et al 2001;Gauthier et al 2002). This scenario is more likely if the original deformation was associated with diagenetic alteration, either dissolution, or partial cementation, such that, when the stress state was altered, bridges between vugs along the fracture path helped to prop open a conductive path.…”