3D Imaging Of The Pore Network In The Shuaiba Reservoir, Al Shaheen Field

Abstract

Abstract Carbonate reservoir rocks often possess highly complex pore spaces, exhibiting extreme heterogeneity in the size, shape and connectivity of their pores at multiple scales. These variable features strongly impact oil recovery and pose severe challenges to reliable measurement and simulation of flow properties. As a complement to parallel studies of the plugs by conventional petrographic and core analysis techniques, a set of samples from four wells in the Shuaiba reservoir of the Al Shaheen field was analysed by 2D mineral mapping (from QEMSCAN) of polished plug sections, and by 3D tomographic mapping (from micro-CT) of subsampled mini-plugs, as a complement to parallel studies of the plugs by conventional petrographic and core analysis techniques. QEMSCAN showed a high variability in measured porosity and pyrite content over all sampled length scales, from millimetres (across the polished plug faces) to feet (with depth in a given well) to kilometres (across the four wells). The porosity from QEMSCAN was generally found to be in good agreement with that measured on the conventional plugs. Two mini-plugs of 5 mm diameter were scanned using helical micro-CT, one of which was subsequently analysed to segment the macropores, microporosity, calcite and pyrite. Comparison with the QEMSCAN results from the section of the "parent" plug showed consistency in estimated porosity and pyrite content between the two methods. Simulations of conductivity and absolute permeability were performed on subvolumes of the segmented tomogram, and displayed a strong variability with the location and size of the chosen subvolume, although the overall trends remained in good agreement with core analysis. Introduction Over the past decade, the rapid developments in X-ray computed tomography (CT), micro-tomography (micro-CT) and sophisticated algorithms for processing tomographic datasets and performing modelling and simulation on them have given rise to the disciplines of digital core analysis and computational rock physics (Knackstedt et al. 2009; Dvorkin et al. 2011). Their aim is to acquire a sufficiently detailed 3D description of a rock sample, spanning the relevant length scales (Sok et al. 2010), to calculate its bulk, elastic or fluid and electrical transport properties. Such analyses give enhanced insight into how the chain of molecular-, pore- and plug-scale characteristics and responses give rise to the core-scale properties measured in laboratories. They may also represent the only alternative for samples on which physical core analysis is unreliable or infeasible. Most pertinently, digital core analysis of multi-phase flow (Oren and Bakke 2003) offers the promise of improved power to predict the recovery of hydrocarbon resources. This approach is especially promising for carbonate reservoir rocks, which often exhibit extreme heterogeneity in the size, shape and connectivity of their pores. Carbonate waterflooding can be strongly impacted by pore types as disparate and intermixed as microporosity, vugs and fractures, for which our vocabulary of geological/petrophysical classifications (Dunham 1962; Choquette and Pray 1970; Lucia 1995) is an insufficient basis for prediction of completeness or rates of oil recovery (Kamath et al. 2001; Graue and Bogno 1999).