An Innovative Approach To Integrate Fracture, Well Test and Production Data into Reservoir Models

Abstract

This paper presents an innovative approach to integrate fracture, well test and production data into the static description of a reservoir model as an input to the flow simulation. The approach has been successfully implemented into a field study of a giant naturally fractured carbonate reservoir in the Middle East. This study was part of a full field integrated reservoir characterization and flow simulation project. The main input available for this work includes matrix properties, fracture network, well test and production data. Stochastic models of matrix properties were generated using geostatistical methodology based on well logs, core, seismic data and geological interpretation. Fracture network was described in the reservoir as lineaments (fracture swarms) showing two major fracture trends. The network and its properties, i.e., fracture porosity and permeability, were generated by reconciling seismic, well logs, and dynamic data (well test and PLT). The challenge of the study is to integrate all the input in an efficient and practical way to produce a consistent model between static and dynamic data. As a result, it is expected to reduce the history matching effort. This challenge was solved by an innovative iterative procedure between the static and dynamic models. The static part consists of the calibration of model permeability to match the well test permeability. It is done by comparing their flow potentials, kh. In this analysis the dominant factor in controlling production at each well, either matrix or fracture, was determined. Based on the dominant factor, matrix or fracture permeability was modified accordingly. This way the changes in permeability are kept inline with the geological understanding of the field. The dynamic part was carried out through a full field flow simulation to integrate production data. The flow simulation at this stage was used to match production capacity, i.e. to determine whether the given permeability (matrix and fracture) distribution is enough to produce the fluid at the specified pressure during the producing period of the well. The iteration is stopped once a reasonable production capacity match is obtained. In general, a good match was achieved within 3–4 iterations. The generated reservoir description is expected to substantially reduce the effort required to obtain a good history match. Introduction This paper presents the approach, implementation and results of fracture integration process into a reservoir model. The study is part of a fully integrated reservoir characterization and flow simulation study of an oilfield in the Middle East. A comprehensive integrated reservoir characterization was conducted by considering all available data, namely well logs and cores, geological interpretation, seismic (structures and inversion derived porosity), fracture network, and pressure build up tests. The approach used in the study was a stochastic approach where multiple reservoir descriptions were generated to quantify the uncertainty in the future performance.1,2 Reservoir properties for each realization were generated using a geostatistical technique that produces properties, i.e., porosity, permeability and water saturation, consistent with the underlying rock type description. The description was based on core and log data. Additionally, porosity, which affects the permeability description, was also constrained to the seismic derived porosity. The permeability distribution generated by this method was referred to as the core-derived permeability in this paper. Since core-measurement commonly represents the matrix property of the rock, the core-derived permeability mentioned above was also referred to as matrix permeability.

Permeability From Production Logs - Method and Application

“…Record up and down passes with the PLT at the end of the transient. 5. Place the PLT between at the point of maximum crossflow that was observed in step 1 (this is usually the same location drawdown number 2.…”

Waterflood performance evaluation in a chalk reservoir with an ensemble of tools

“…Many authors reported integrating surveillance data with full-field simulation studies. Some of these studies include those of Hustedt and Snippe (2010), Langaas et al (2007), Bahar et al (2005), and King et al (2002), among others over the last decade.…”