Field X comprises a giant Palaeogene limestone reservoir with a long production history. An original geomodel used for history matching employed a permeability transform derived directly from core data. However, the resulting permeability model required major modifications, such as horizontal and vertical permeability multipliers, in order to match the historic data. The rationale behind these multipliers is not well understood and not based on geological constraints. Our study employs an integrated near-wellbore upscaling workflow to identify and evaluate the geological heterogeneities that enhanced reservoir permeability. Key among these heterogeneities are mechanically weak zones of solution-enhanced porosity, leached stylolites and associated tension-gashes, which were developed during late-stage diagenetic corrosion. The results of this investigation confirmed the key role of diagenetic corrosion in enhancing the permeability of the reservoir. Insights gained from the available production history, in conjunction with petrophysical data analysis, substantiated the characterization of this solution-enhanced permeability. This study provided valuable insights into the means by which a satisfactory field-level history match for a giant carbonate reservoir can be achieved. Instead of applying artificial permeability multipliers that do not necessarily capture the impacts of geological heterogeneities, our method incorporates representations of fine-scale heterogeneities. Improving the characterization of permeability distribution in the field provided an updated and geologically consistent permeability model that could contribute to the ongoing development plans to maximize incremental oil recovery.

Obtaining a fit-for-purpose rock-type classification that adequately incorporates the key depositional and diagenetic heterogeneities is a prime challenge for carbonate reservoirs. Another prevailing issue is to integrate the static and dynamic data consistently with the rock-typing scheme in order to correctly initialise the reservoir flow simulation model. This paper describes a novel near-wellbore rock-typing and upscaling approach adopted to address the crucial challenges of integrating reservoir rock-typing and simulation in carbonate reservoirs. We demonstrate this workflow through a case study for a highly heterogeneous Eocene-Oligocene limestone reservoir, Field X. Geological studies carried out in Field X suggested that the key permeability pathways are strongly related to the mechanism of reservoir porosity and permeability evolution during late-burial corrosion. The rock-typing and upscaling methodology described in this paper involves the geological-petrophysical classification of the key reservoir heterogeneities through systematic evaluation of the main paragenetic events. Associations between the depositional and late-burial corrosion features, and their impact on reservoir flow properties, were accounted for in our workflow. Employing near-wellbore rock-typing and upscaling workflow yielded consistent initialisation of the Field X reservoir simulation model and therefore improved the accuracy of fluids-in-place calculation. Subsequently, the cumulative production curves computed by the reservoir simulation model of Field X showed closer agreement to the historic production data. The revised Field X simulation model is now much better constrained to the reservoir geology and provides an improved geological-prior for history matching.

Carbonate reservoirs host a major portion of the world's remaining conventional and unconventional hydrocarbon reserves, typically containing multi-scale geological heterogeneities varying over many orders of magnitude in size. Characterizing and representing them robustly in reservoir models is a prime challenge in carbonate reservoir simulation. One of the key aims of this paper is, hence, to present a novel near wellbore upscaling (NWU) workflow that addresses the challenges associated with conventional carbonate modelling workflows. The NWU workflow provides a systematic geostatistical approach to obtain more realistic representation of multi-scale geological-petrophysical heterogeneities in complex carbonate reservoir simulation models. Using well log and core data, near wellbore regions were recreated to represent the core scale heterogeneities via high resolution geostatistical models. These core/centimeter scale permeability models were then upscaled into wireline/decametre scale using flow-based upscaling. The results, coupled with wireline data were used to generate global porosity-permeability and vertical-horizontal permeability relationships for reservoir simulation. Importantly, the workflow mitigates sample bias, which is frequently observed in the core data for carbonate reservoirs. We have applied our approach to a mature carbonate field, to model and upscale crucial multi-scale heterogeneities ubiquitous in the reservoir. These heterogeneities, such as mechanically weak zones of enhanced micro- and macro-porosity, leached stylolites and associated tension gashes, were caused by diagenetic corrosion. Core plugs representivity is always an issue in carbonates and these highly corroded features were very difficult, if not impossible, to sample due to their fragility. As a result, the field suffers from inherent sample biasing and insufficiency of Routine Core Analysis (RCA) data, consequently underestimating the permeability in the simulation model. The workflow presented here has enabled the authors to re-evaluate the reservoir permeability model by accounting for as yet under-sampled geological heterogeneities. The paper represents a focused individual study addressing this specific issue and doesn't necessarily reflect the operator's full understanding of this multifaceted field. Our new permeability model has addressed the need for artificial permeability multipliers and provided insight on the potential causes of the original mismatch. As a result, a new alternative model scenario has been built to help guide the on-going development plans and forecasting incremental oil recovery.