Tag: sedimentology

A Procedure to Parameterize High Permeability Zones in Naturally Fractured Reservoir

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This paper presents a novel-methodology to compensate for the poor characterization of high-permeability structures (excess-K: vugs, karsts and super-K features), and non-fault-related-fractures, in naturally fractured Brazilian Pre-Salt carbonate reservoirs. These heterogeneities are often undetectable in well logs and seismic data, but significantly impact well performance. The methodology aims to enhance the representation of such features within dynamic simulation models, improving reservoir characterization and supporting more reliable data-assimilation and forecasting processes. The methodology involves: (1) upscaling high-fidelity fine-grid models to coarser-grids while preserving dynamic behavior, (2) identifying wells with productivity/injectivity mismatches due to a poor excess-K characterization, (3) applying a data assimilation (DA) process to minimize the mismatch between modeled and measured wells production and injection rates by updating the absolute permeability of the matrix. The novelty of the process is that the permeability field is updated by creating a mask (3D property) built by kriging permeability increments estimated from the well cells with productivity/injectivity issues. Therefore, the DA aims to find the least increments of permeability needed for each well such that when this mask is summed with the matrix permeability field all wells present good productivity/injectivity matching with history data. The methodology was applied to a dual-porosity/dual-permeability (DP/DK) compositional reservoir model. Two distinct well behaviors were observed: (1) wells located within fracture zone (12 of 33) showed good productivity/injectivity alignment with historical data and (2) the remaining 21 wells, located away from fracture zone, exhibited significantly poorer productivity/injectivity. This mismatch was attributed to the absence of excess-K features in the original matrix permeability model (Km-field). The optimization process was applied to these 21 wells. For each well a specific Ki-value was settled, defining input-points for kriging. The resulting kriged permeability correction volume (mask) was summed with the Km-field to generate an updated-permeability model. This process was repeated until all wells presented good productivity/injectivity matching with historical data. The process not only corrected the simulated dynamic responses, but also revealed key spatial permeability patterns that had not been captured in the static model. The results served as feedback to the geologists and enabled iterative improvement of the geological model, supporting a more integrated and realistic characterization. Overall, the results validate the methodology as a robust tool for incorporating unresolved high-permeability features in reservoir simulation and improving the quality of data assimilation. This study introduces an automated, iterative probabilistic data-assimilation framework that directly integrates geostatistical kriging with permeability adjustments for excess-Kstructures. The approach provides bidirectional feedback to geological modeling and allows the generation of realistic ensembles for data assimilation workflows. By combining geo-statistics within an uncertainty reduction scheme, the method addresses key modeling gaps encountered when modelling a Brazilian Pre-Salt carbonate.

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.