Tag: flow in porous media

Integrated Multi-Scale Pore Characterization of Carbonate Rocks in the Barra Velha Formation, Santos Basin, Brazil

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Carbonate rocks feature heterogeneous porous systems that span multiple scales, from pore level to the reservoir scale. The complexity and diversity of carbonate reservoirs demand a consistent approach to their characterization. The efficient integration of multiscale imaging data and petrophysical data is increasingly important to address the challenges associated with these complex carbonate reservoirs. A crucial step in overcoming these scale gaps in reservoir modeling and simulation involves enhancing the characterization of reservoir flow units and their associations with geological and petrophysical heterogeneities at varying scales. In this study, we focus on the classification of pore types using digital rock analysis and petrophysical evaluation of pre-salt lacustrine carbonates from the Barra Velha Formation (BVF) in the Santos Basin using computerized tomography (CT), core samples description, and petrography. Eight types of pores were identified at the core scale: interparticle, stratiform-vuggy, growth framework, vuggy, vuggy-fracture, fracture, interclast, and intraclast. The distribution and characteristics of these pore types were analyzed at different scales, including thin-sections and micro-CT, and nuclear magnetic resonance (NMR), which highlights the diversity in the porous system and the impact of different pore types on porosity and permeability. NMR analyses illustrated the pore size heterogeneity to provide distinction between tight and porous samples. Hydraulic rock units (HRUs) were defined based on flow zone indicator (FZI) using the probability plot approach. Seven HRUs were defined: HRU1 and HRU2 represent samples with the highest FZI and rock quality index (RQI) values, whereas HRU3 and HRU4 denote intermediate values. HRU5, HRU6, and HRU7 represent units with the lowest values. HRU1 and HRU2 were predominantly associated with vuggy, growth framework, and interparticle porosities, which are often enhanced by dissolution processes. Conversely, HRUs with reduced reservoir qualities (5, 6, and 7), characterized by the lowest permeability values, are more prevalent in intervals with higher silicification and silica and dolomite cementation, presenting a variety of pore types at a macroscale. The integration of multiscale imaging techniques and petrophysical data underscores the complexity of pore systems, providing crucial insights into their reservoir characteristics.

Construction of Single-Porosity and Single-Permeability Models as Low-Fidelity Alternative to Represent Fractured Carbonate Reservoirs Subject to WAG-CO2 Injection Under Uncertainty

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Fractured carbonate reservoirs are typically modeled in a system of dual-porosity and dual-permeability (DP/DP), where fractures, vugs, karsts and rock matrix are represented in different domains. The DP/DP modeling allows for a more accurate reservoir description but implies a higher computational cost than
the single-porosity and single-permeability (SP/SP) approach. The time may be a limitation for cases that require many simulations, such as production optimization under uncertainty. This computational cost is more challenging when we couple DPDP models with compositional fluid models, such as in the case of fractured light-oil reservoirs where the production strategy accounts for water-alternating-gas (WAG) injection. In this context, low fidelity models (LFM) can be an interesting alternative for initial studies. This work shows the potential of compositional single-porosity and single-permeability models based on pseudo-properties (SP/SP-P) as LFM applied to a fractured benchmark carbonate reservoir, subject to WAG- CO2 injection and gas recycle. Two workflows are proposed to assist the construction of SP-P models for studies based on (i) nominal approach and (ii) probabilistic approach of reservoir properties. Both workflows begin with a parametrization step, in which the pseudo-properties are optimized for a base case in order to minimize the mismatch between forecasts of the SP/SP-P and DP/DP models. The new parametrization methods proposed in this work showed to be viable for the construction of the SP/SP-P models. For studies under uncertainties, the workflow proposes obtaining pseudo-properties by robust optimizations based on representative models from a DP/DP ensemble, which proved to be an effective method. The case study is the benchmark UNISIM-II-D-CO with an ensemble of 197 DP/DP models and two different production strategies. The risk curves for production, injection and economic indicators obtained from DP/DP and SP/SP-P ensembles showed good match and the computational time spent on simulations of the SP/SP-P ensemble was 81% faster than DP/DP models, on average. Finally, the responses obtained from both ensembles were validated in a reference model (UNISIM-II-R) that represents the true response and is not part of the ensemble. The results indicate the SP/SP-P modeling as a good LFM for preliminary assessments of highly time-consuming studies. Besides, the workflows proposed in this work can be very useful for assisting the construction of SP/SP-P models for different case studies. However, we recommend the use of the high-fidelity models to support the final decision.