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Geological Society, London, Special Publications; 1992; v. 65; p. 31-42;
DOI: 10.1144/GSL.SP.1992.065.01.04
© 1992 Geological Society of London

Sedimentology and Stratigraphic Correlation

Sedimentological borehole image analysis in clastic rocks: a systematic approach to interpretation

Lawrence T. Bourke

Reservoir Studies Group, Schlumberger Data Services, Woodlands Drive, Dyce, Aberdeen AB2 0ES, UK

Detailed study over the four years since the introduction of the Formation MicroScanner Tool* (FMS) has resulted in the evolution of a systematic interpretation approach to the extraction of a formal sedimentological description of extensive reservoir intervals using borehole images in clastic sediments. This approach takes account of thorough log quality control and the recognition of non-geological artifacts and involves the integration of the available open hole logs to establish lithology, along with the incorporation of core or sidewall cores as ‘hard’ lithological and textural data to ensure interpretation confidence.

The approach is practical and straightforward. However, a workstation provides significant advantages to the skilled interpreter compared with a paper-based analysis. After quality control and recognition of artifact images, five interpretation steps are suggested. (i) Fine-calibrate open hole logs (conventional lithology indicators) from sidewall and conventional core samples. Enhance lithology recognition using dipmeter resistivity curves. (ii) Annotate the above lithological information onto FMS images. (iii) Constrain feature recognition from images using local geological knowledge. (iv) Pick and classify feature dips, then check dip category validity by generating dip and azimuth histograms. Reclassify as necessary. (v) Extract relevant sedimentary and lithological data from images to construct a conventional sedimentological facies description.

One of the key aspects of borehole image analysis is the development of an interpreter’s skill in recognizing geological features from microresistivity images. Finally, aspects of core reconciliation such as depth matching are considered.





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