MICP-Based Elastic Rock Typing Characterisation of Carbonate Reservoir

Abstract

A workflow applied to achieve a multi-scale characterisation of a carbonate reservoir is presented. Carbonate rocks are strongly heterogeneous due either to complexity of the primary fabric or to diagenetic over-printing. The combination of these features leads to complicated pore systems, thus a proper definition of pore types using either pore size or pore throat size distributions, is important to indirectly capture diagenetic modifications and to get a link to dynamic properties. A new approach was developed in order to define a Rock Type classification (RRT) each time the approaches based on Winland's and Hydraulic Flow Unit methods do not give a reliable core facies characterisation when moving to the log scale. Moreover, the proposed workflow accounts for stratigraphy and seismic since RRT are linked to the elastic properties. In the new MICP-based Rock Typing workflow, RRT are identified by describing dominant pore types using mercury injection (MICP) curves parameterisation and routine core data (RCA). Clustering and subsequent extrapolation of MICP derived RRT to RCA samples, are the first two stages to achieve a predictable classification into the log domain. Log RRT are then defined at the log scale using curves of elastic properties, like Poisson's Ratio (PR), Frame Stiffness (fk) and Flexibility (γk) Factors. These elastic parameters (calculated with the Extended Biot Theory), can capture the effects of pore structure on the petrophysical properties and link RRT prediction at well position to seismic attributes. Since the RRT are characterised in the elastic space, the facies model – properly upscaled – represents the basis to classify elastic attributes from seismic inversion in a Bayesian framework. The seismic classification can then be used as a driver for RRT distribution in the inter-well space into the 3D model. A further benefit is the direct relationship to the original RRT porosity/permeability distributions, when modelling petrophysical properties. This new workflow was a successful solution to define homogeneous reservoir intervals in a carbonate environment characterised by the lack of a significant relationship between depositional facies and petrophysical properties.

Insights into the Effects of Pore Size Distribution on the Flowing Behavior of Carbonate Rocks: Linking a Nano-Based Enhanced Oil Recovery Method to Rock Typing

“…Conventional reservoir rock typing has been defined as the classification of the reservoir rock based on its petrophysical properties acquired through wireline logs, porosity-permeability correlations, mercury injection curves, and geological features [ 5 , 16 , 17 , 18 , 19 , 20 ]. As a basis for reservoir rock classification, the pore geometry can be assessed based on the capillary pressure, which, in turn, can be better measured by the mercury injection analysis rather than other methods [ 21 ]. Most of the aforementioned research works have pointed out the relationship between the PSD and the residual oil saturation based on the analyses performed on a synthetic structure (i.e., micro model or sand-packs), making their results unreliable for using in actual reservoir studies.…”