ABSTRACT Facies characterization in carbonate reservoirs remains challenging due to their pronounced textural and structural heterogeneity. Variations in grain packing, cementation, and diagenetic overprints produce contrasting acoustic responses in borehole image logs, often limiting the reproducibility of facies interpretation. Because continuous coring typically covers less than 5%–10% of a well, high‐resolution acoustic image logs have become a key source of data for characterizing borehole wall textures and structures, enabling the recognition of recurring image facies patterns in both cored and non‐cored intervals. This study proposes a systematic and reproducible workflow for the classification and calibration of carbonate and volcanic image facies through the integration of acoustic image logs, core observations, and computed tomography (CT) images of cores. The methodology follows eight sequential steps designed to progressively improve rock‐log calibration and interpretative consistency. Image logs are first processed to ensure data quality, followed by CT image generation from recovered cores. Depth matching is then performed using gamma ray curves, complemented by fine‐scale alignment based on traceable textures observed in both datasets. Sidewall samples are subsequently repositioned to refine their depth reference. Edge‐contrast attributes are computationally extracted to enhance structural and textural boundaries, after which image facies are calibrated in intervals with rock control and extrapolated to non‐cored intervals. Nine lithofacies from the pre‐salt section of the Santos Basin were recognized and display characteristic acoustic textures at image log scale. Laminites typically appear as thin, parallel amplitude contrasts that may become massive when lamination thickness falls below tool resolution. Spherulitites display granular to laminated textures, whereas stromatolites exhibit laminated or domal geometries. Grainstones and rudstones show granular acoustic textures, with rudstones presenting coarser patterns and stronger amplitude contrasts. Carbonate breccias display chaotic acoustic textures related to structural disruption and diagenetic modification. Volcanic image facies also show distinctive responses, with massive volcanic rocks presenting homogeneous high‐amplitude textures, amygdaloidal or vesicular varieties displaying heterogeneous patterns associated with mineral‐filled cavities, and volcanic breccias showing discontinuous and high‐contrast acoustic signatures. Quantitative analysis indicates that image facies interpreted as reworked deposits dominate several intervals (45%–65%), whereas facies interpreted as in situ deposits prevail in others (49%–71%). Volcanic intervals, including basement units, occur locally and exhibit distinctive acoustic signatures. The proposed workflow reduces interpretative subjectivity, improves reproducibility, and strengthens the integration between borehole imaging, rock data, and petrophysical analysis, contributing to reservoir characterization in heterogeneous carbonate systems.
Fioriti et al. (Mon,) studied this question.