The Ekofisk Field is a naturally fractured chalk reservoir located in the Norwegian sector of the North Sea. The natural fractures clearly control the permeability distribution, as the effective permeability can reach 50 mD whereas the matrix permeability only ranges between 0.1 mD and 10 mD. Permeability mapping in this field has been challenging due to the structural, stratigraphic and mineralogical complexity, tectonic history and non-negligible matrix permeability. A detailed fault interpretation has resulted in a complex fault pattern. A fault intensity (P21) parameter calculated from the fault pattern has proved to be the critical component for permeability mapping. Correlations were found between the fault intensity (P21) values and (1) the fracture distributions from cores and logs at individual wells, and (2) the fracture component of the well test permeability ( K frac – total permeability less matrix permeability). These relationships allowed field-wide fracture permeability maps to be developed based on the P21 results. Total permeabilities were obtained by summing the matrix permeability and the calculated fracture permeability. These permeability maps were introduced in the Ekofisk Flow Model 2002 and refined to match the rate performance of the 50 initial wells run in prediction mode (well head pressure constraint). The runs in prediction mode have proved to be very effective for calibrating the permeability distributions, based on initial well performance above the bubble point. This simulation technique was extended to cover all producers (262 wells) during the entire history of the field to refine the maps further. After calibration with the performance data, a satisfactory history match was obtained by making minor changes to permeability and other dynamic parameters. Additionally, the running of the model of the mature Ekofisk Field in prediction mode for its full field life has provided a robust tool for calibrating field performance.
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.
Characterising and modelling of naturally fractured reservoirs (NFR) with fracturing at different scales is usually a challenging task as the specific response from each scale is difficult to isolate. We focus on a carbonate reservoir in North Africa, in production for two years. There is evidence of fracturing at different scales (from diffuse fractures to conductive faults) with significant implications for oil production. We first present the way fractures have been fully characterised using an extensive integration of static (FMI) and dynamic (Well test, Pressure Build Up, Mud losses) data. The advanced use of well test signatures in understanding the main flow mechanisms occurring within the reservoir is emphasized. Then, we detail the way the dynamic model was build using a novel discrete fracture network (DFN) approach developed internally. The method populates the static parameters at the full field scale using a geo-statistical process guided by a geological driver. Using an innovative technique (the Elementary Patch), a fast calculation of fracture permeability in each grid cell and automatic calibration on the well test data can be made. We also discuss how the best choice for the simulation model (single porosity vs double porosity) depends not only on the fracture-to-matrix permeability ratio but also on the magnitude of the shape factor and on the production mechanism. The final dual porosity-dual permeability model integrates the intermediate scale fractures implicitly and the conductive faults explicitly whereas the smallest scale is discarded as it has a negligible impact. In summary, we present a complete and innovative workflow process for a geoscience study on NFR and demonstrate its application in a real case study. The need for full data integration to achieve a comprehensive understanding of the flow mechanisms involved during production is underlined. Introduction and scope The full workflow of a fracture study from characterization to modeling on a field operated by TOTAL in Africa is described in this paper. Particular attention is given to the integration of static and dynamic data and the way it allowed us to achieve a satisfactory characterization of the fracture network. A new DFN tool developed by TOTAL has been used for the modeling of this field. For confidentiality purposes, the field will be designated as reservoir ‘R’ in the paper. The field is an oil and gas accumulation forming a WE anticline truncated to the East by a fault (Fig 1). It is located in a complex folded and faulted transfer zone, active during the reservoir deposition, of Eocene age. The morpho-structural pattern of the transfer zone is constrained by N150 normal faults with possible salt diapir activity paralleling the rifts and bounding 3 sedimentation domains. They cut folds with N80 axes partially interpreted as reactivation of previous normal faults. The western domain of the transfer zone is constrained by tectonic activity during the Eocene reservoirs deposition with:High subsidence under open lagoonal and marine influence characterized by thick Upper ‘R’ Nummulitic limestone facies limited to paleo-highs generated by the growing anticlines.Thin, low energy, bioclastic limestone and dolomite in Lower ‘R’. The field was appraised by three wells. W01, drilled vertically on the crest, found gas in the Upper ‘R’ and oil in the Lower ‘R’. W02, drilled vertically on the flank, was water bearing. W03, drilled slanted and up dip of W02, crossed the WOC and triggered the decision to develop the field since it proved an overall oil thickness of 220m and exhibited characteristics even better than those encountered in W01. The total reservoir thickness is around 250m and most of the oil lies in the Upper ‘R’. The dip varies from 4° westward to 30° on the northern and southern flanks. Rock data show better properties in the Upper (f=17%, k=30mD) than in the Lower (f=12%, k=5mD). This field has been on stream since 2003. It is currently producing at a plateau of 40000 bopd through 5 horizontal and 1 vertical wells. Additional wells and gas re-injection are planned. In this context, a good characterization of the fractures was deemed critical.
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