Josselin Kherroubi

Borehole image correspondence and automated alignment

Borehole images are often misaligned due to a depth offset in the acquisition sensors of a wireline tool. We propose an algorithm that identifies matching feature points and aligns the image. One of the main challenges is that imaging pads have no azimuthal overlap. This has been solved by extrapolating the pixels on the boundary to create a synthetic overlap that facilitates feature matching. Feature matching is implemented in two stages: first by finding a local correspondence among feature points and second by performing a global minimization with additional regularization constraints on the estimated shifts. The method has been successfully used to align several imaging logs in less than 1 minute whereas a manual alignment would take 6 hours.

Comprehensive Texture and Porosity Quantification from Electrical Borehole Images

SUMMARY The porosity system is very complex in carbonates. It is well known that the pore space connected to fractures, solution enhanced bedding planes, and vugs (vug to vug) greatly enhance the fluid flow, compared with the pore space in isolated vugs. We propose a new workflow which combines existing methods to quantitatively characterize these different pore spaces from electrical borehole images. The workflow starts with an image calibration and a gap-filling for wireline images. After extracting the formation matrix, conductive and resistive heterogeneities are automatically delineated on the image using thresholds on contrast (against matrix) and value. By superimposing fracture traces, bed boundaries, and heterogeneity-connecting crest lines on the heterogeneity image, it is possible to automatically classify the full range of the heterogeneities. The geometry and the electrical properties of each of the heterogeneous features and the intensity of their connectedness are characterized. A porosity map is subsequently computed using an established method and the map is associated with the heterogeneities. In this way, the porosity of each heterogeneity type can be evaluated. Case studies have demonstrated that the workflow can provide quantitative measures of important reservoir parameters from electrical borehole images to better evaluate the fluid flow.

Applications of Borehole Images for Optimal Completion in Shale Plays

Operators are drilling horizontal wells and performing multi-stage completions to produce large quantities of hydrocarbon from shale reservoirs. However, applying these technologies may not yield consistent, economic production. The causes for poor performance in horizontal wells are: poor placement, completed geometrically, without accounting for changes along the wellbore in rock matrix (reservoir quality, RQ) or stresses (completion quality, CQ), or hydrocarbons and associated pore pressure expulsed through fracturing and/or matrix leak-off. The purpose of this paper is to show the applications of borehole images to optimally place and complete horizontal well in shale plays. Images provide critical information to address RQ and CQ. Images are collected from vertical wells and, together with other tools, aid in the identification of the optimum zone for lateral placement in terms of superior RQ and CQ. The main applications of images on lateral wells are: well placement, mapping structural complexity, capturing the orientation and densities of natural and induced fractures, etc. Changes in these properties will have significant ramifications on the horizontal completion. Borehole images have the potential to provide most of the information needed to steer and place horizontal wells properly, maximizing reservoir contact and permitting an engineered completion that ensures optimized production.