Dynamic Behavior of Discrete Fracture Network (DFN) Models

Abstract

Abstract This work shows that discrete fracture network modeling is very desirable for the characterization of naturally fractured reservoirs but it is only a highly subjective starting point. Thus, calibration against short and long term pressure transient tests is most crucial. This paper shows how the dynamic behavior of a discrete fracture network model of Margarita gas field compared against pressure transient measurements in a sidetrack delineation-well. The performance comparison of a very fine-grid reservoir model, which included the discrete fracture network information, versus a much coarser upscaled grid model is also documented. Introduction Geological reservoir characterization is the most crucial first step in construction of a credible reservoir flow model for naturally fractured reservoirs. The most notable approaches for constructing a geological model of a reservoir include classical deterministic methods, where geologists make the best interpretation from existing data and build a model of the reservoir. In the last several years, however, deterministic approaches have been complemented by quantitative geostatistical approaches such as multipoint statistics (MPS) and discrete fracture network (DFN) modeling.1,2,3 The MPS generates a depositional and lithofacies model of a reservoir by incorporating geological architecture and properties of the rock fabric and is touted as a very promising stepping stone in construction of viable numerical reservoir flow models.1 However, for reservoir modeling purposes, the flow units and fracture flow paths must be included in the depositional model.4 The DFN modeling is often used to accomplish the latter. Both the deterministic and geostatistical techniques, however, are highly subjective and, while such fundamental geological modeling techniques are often the necessary starting points, any revisions toward the construction of the ultimate reservoir flow model would depend on calibration against reservoir performance as well as carefully designed flow tests.5 In fact, an ultimate reliability standard for viability of any reservoir characterization model is calibration against dynamic data from several wells. This implies that reservoir characterization life cycle is an iterative process as new static and dynamic data become available. Experience in naturally fractured reservoirs (NFR) has indicated that low permeability formations often produce fluids through open fractures, which intersect the wellbores. This paper illustrates fluid flow through individual fractures intercepted by a vertical well, initially estimated using a parallel plate method, finding that contribution of each fracture need to be calibrated to a production test. The composite summation of individual fractures along the wellbore allowed the construction of a synthetic PLT profile. A horizontal sidetrack from the vertical well was planned to improve the well's productivity. A discrete fracture network (DFN) model, generated around the area of influence of the well, was used to identify the best direction for the sidetrack interval (perpendicular to the most open main fracture planes) and to predict the type of the fractures to be intercepted. After the sidetrack was drilled, fracture types (hierarchy by aperture) were identified and classified using an ultra sonic borehole image tool. The DFN fracture model was calibrated against a pressure buildup test conducted in the sidetrack well, using dual-porosity numerical simulation over a very fine grid model. The calibration studies showed that the aperture-based effective transmissivity was significantly greater than the actual well test transmissivity while the estimated fracture storativity was significantly lower than the actual well test value. Dynamic upscaling of the fine-grid model was performed to evaluate whether the upscaled models would preserve the well/reservoir behavior of the fine-grid models. Margarita Field General Characteristics The Margarita structure is located in the southern Bolivian Subandean, on the structural trend of the Suaruro Range, 35 km to the west of Villamontes town.6–8 The Margarita Field lies in the Caipipendi Block (Fig. 1) operated by Repsol-YPF with 37.5% equity. Partners are BG International (37.5%) and Pan American BP (25%). The field is located in the northern part of an elongated anticline oriented NNE-SSW, and is 30 km long and 9 km wide. The closure of the field consists of several compartments separated by reverse faults.