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. Field X is a giant offshore oil and gas field with a long production history from a limestone reservoir. Permeability has been identified as one of the biggest uncertainties associated with the reservoir simulation model during field optimization studies that have been carried out by the operator previously. A reduction in the uncertainties for the permeability distribution is needed to evaluate the feasibility of the next development phase.In this study we attempt to resolve these issues through a systematic re-evaluation of the reservoir simulation model, considering, in particular, the field's diagenetic history. Our aim is to understand the fundamental controls on fluid flow that need to be adequately captured in the reservoir model. Geological studies carried out by the operator suggest that the key permeability pathways are strongly related to the mechanism of reservoir porosity -permeability evolution during late-burial corrosion (Wright & Barnett 2011). Late-burial corrosion in Field X is referred to as deep burial/ mesogenetic corrosion associated with the corrosion of limestone by burial-derived (hypogene) fluids. However, it is unclear how a diagenetic model that accounts for late-burial corrosion should be included in the reservoir simulation model and how such an updated reservoir simulation model could i...
The Panna–Mukta fields host hydrocarbons in the Bassein Formation Eocene–Oligocene ramp limestones. The pore system is almost wholly secondary, comprising microporosity, mouldic porosity, vugs, solution-enlarged stylolites and fractures. Although petrographical evidence points to dissolution after extensive late cementation, the presence of a high permeability layer close to a palaeokarstic surface at the Eocene–Oligocene boundary has raised the possibility that this secondary porosity could be related to subaerial exposure. However, the Panna–Mukta reservoirs show a strong correlation between secondary matrix porosity and stylolite density measured from cores. Stylolites only developed in ‘clean’ limestones lacking argillaceous material, whereas more argillaceous limestones in the succession are characterized by dissolution seams and have poor reservoir quality. These cleaner limestones occur preferentially below the Eocene–Oligocene boundary, representing an upwards-shallowing sequence, whereas the argillaceous limestones occur further below the Eocene–Oligocene boundary in the lower part of the same shallowing-upwards sequence and in the transgressive limestones at the base of the Bassein A. This secondary porosity distribution suggests movement of corrosive fluids along pre-existing stylolites. Despite an apparent link between porosity distribution and an unconformity, secondary porosity development was mesogenetic and related to the distribution of facies that favoured stylolites that acted as conduits for the flow of corrosive fluids. The Bassein Formation reservoirs show unequivocal evidence of significant porosity development by mesogenetic dissolution but the exact process or processes by which such porosity creation occurs requires further work.
New reservoir characterisation methods are needed to integrate multi-scale exploration and development data, particularly at the interface between well and field models. In this paper we illustrate a novel workflow involving high resolution Near Wellbore Modeling (NWM), which allows us to accurately include seismic, wire-line data, FMI, and well core logs from multi-porosity reservoirs in field-scale reservoir simulations. We demonstrate that NWM improves reservoir characterization and production management. The workflow was applied to a realistic clastic reservoir with high variance at small scale and can also be extended for carbonate reservoirs. We have performed a number of sensitivities comparing conventional local grid refinement in the near wellbore region with that involving NWM and obtained a significant increase in the accuracy of reservoir characterization and the calibration of dynamic models. Centimetre-scale models, containing several million cells, representing the fine geological details of the near-wellbore region were constructed using available data from seismic, core, open-hole and production well-log suits. Sensitivities were performed using these high-resolution models to obtain regular grids with the best possible up-scaling. The resulting well models were imported into a field-scale simulation model to evaluate the dynamic behavior of the reservoir employing numerical well testing. Our results show that using NWM tools for reservoir modeling yields more precise flow calculations and improves our fundamental understanding of the interactions between the reservoir and the wellbore.
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.
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