Evaluation of Karst Porosity Morphological Properties through Borehole Image Logs – Correlation with Dynamic Reservoir Properties from a presalt Oil Field

Abstract

The representation of karst petrophysical properties on geologic models has been a challenge, mostly because of the lack of reliable information about the mega and giga pore network, such as large vugs, caves, conduits and enlarged fractures. Since image logs currently have provided the capability of measuring morphological properties in this pore scale, specific techniques have been developed with the objective of obtaining quantitative data that capture these properties. In order to evaluate morphological properties that are representative of mega and giga pores, it is necessary to individually segment each pore structure. A set of computational geometry and image processing techniques were used to measure morphological properties, such as area, perimeter, longest internal path (LIP), internal length (IL), and structure diameter. The area and perimeter of the structure are computed directly on the segmented borehole image log data. The application of this technique allows the classification of different mega and giga pore types. The quantitative evaluation of karst porosity developed in this work has been applied in a brazilian karstified pre-salt carbonate reservoir. The results have shown good correlation with dynamic properties, such as fluid losses while drilling and high productivity intervals measured in production logs. It was possible to identify two distinct correlations between the increase of pore diameter and permeability response of fractured and vuggy-cavy reservoirs. This new technique is helpful for improving the knowledge and representability of the pore scales in order to honor the complexity of the structures generated by the karstification processes. Additionally, new workflows have been developed to incorporate the pore diameters in the geological modeling of karstified reservoirs. The distinct properties of each medium, in the future, might be represented in a model with the assignment of specific fluid mechanics equations, such as Darcys and Hagen-Poiseuilles, for each one. There is a new ground to be gained in fluid flow simulation at these wide ranges of scales and heterogeneous distribution. For that reason, one of the aims of this paper is to stimulate the petrophysical and geological communities towards this goal, as more representative properties of karst porosity heterogeneity become available.

Geological Insights from Porosity Analysis for Sustainable Development of Santos Basin’s Pre-Salt Carbonate Reservoir

“…Pore size classification plays a pivotal role in understanding the dynamic properties of carbonate reservoirs, as distinct behaviors emerge with varying pore sizes ( [50,51]). Larger pores, for instance, exhibit correlations with fluid losses during drilling or signify intervals of heightened productivity ( [51]).…”

“…Pore size classification plays a pivotal role in understanding the dynamic properties of carbonate reservoirs, as distinct behaviors emerge with varying pore sizes ( [50,51]). Larger pores, for instance, exhibit correlations with fluid losses during drilling or signify intervals of heightened productivity ( [51]). The intricate three-dimensional nature and irregularities of pores, as highlighted by [50], pose challenges in precisely characterizing their sizes visually.…”

Carbonate reservoir characterization with integrated rock, special well logs, and machine learning methods

“…However, for pores above a certain size threshold (>50-100 microns), T2 distribution is no longer sensitive to pore-size, hindering its ability to estimate porosity in vuggy-rich zones (Ramamoorthy et al, 2010). For this reason, Acoustic Borehole Image Logs are a great complementary tool to identify mega and giga-pores in high-dissolution zones de Jesus et al, 2019).…”

“…The histogram from Acoustic Borehole Image Logs generally display a bi-modal amplitude in vuggy-rich carbonates, whereas vuggy-free carbonates show a unimodal amplitude Boyd et al, 2015;de Jesus et al, 2019). A threshold can be set to segment the matrix from vuggy porosity, which is referenced as a Vuggy Porosity Index (Melani, 2019) (Fig.…”

“…Moreover, intervals where vuggy pores reach the size of small caves (larger than the diameter a plug) (Duarte et al, 2018;de Jesus et al, 2019), may impose additional problems. Such zones are generally undersampled because of operational conditions, thus do not have a corresponding RPCA data point.…”