Effective application of geological analogue databases to reservoir facies modelling

Abstract

Sedimentary facies represent a primary control on the distribution of porosity and permeability in siliciclastic reservoirs. Therefore building realistic facies models is important for estimating hydrocarbon volumes in place, forecasting hydrocarbon production and assessing strategies for the development of hydrocarbon fields. As such, facies modelling is routinely employed as an integral part of reservoir modelling workflows designed to populate petrophysical properties in the unknown volumes between and beyond 1D well data. In practice however, facies-model design is subjective, and the appropriateness of chosen facies components and modelling parameters are difficult to validate. To address this loose subjectivity, geological analogue data (outcrop, modern or subsurface) are commonly invoked to constrain facies models. This is a reasonable approach in principle, but there exist problems in connection with the selection of analogues, the type of data they provide, and the ways by which these data are transformed to parameters used as input to facies-modelling algorithms. We present a method designed to overcome these subjective decision steps in order to effectively integrate geological analogue data in reservoir-modelling workflows. An online portal has been developed that enables to quickly filter multiple relevant analogues contained in relational databases of fluvial (FAKTS), shallow-marine (SMAKS) and deep-marine (DMAKS) clastic depositional systems. These relational databases store data on sedimentary units at multiple scales, describing their geometries, their relations with surrounding elements, their hierarchical organization, and their lithological heterogeneity. All the analogues contained in the databases are classified on the geological controls of the depositional systems, contextual information, and metadata, allowing users to select analogues that are most suitable in application to the reservoir at hand. The filtered analogue data is visualised graphically in real time, to enable the user to review database outputs and optimize the selection of inputs to a reservoir model. Subsequently, the filtered analogue data are automatically parameterized to match the requirements of different stochastic facies-modelling algorithms, thanks to workflows for translation of analogue data into model inputs. Where available, the analogue data is directly used as parameters in the modelling algorithm. When parameters are not directly available from suitable analogues, empirical relationships that are established in the scientific literature are used to define base-case input parameters. After review, the parameterized composite analogue can be directly imported into the reservoir modelling package.

AAPG Datapages/Search and Discovery Article #90325 © 2018 AAPG Europe Regional Conference, Global Analogues of the Atlantic Margin, Lisbon, Portugal, May 2-3, 2018