--> Abstract: Prediction of Cobble Occurrence Using Electric Images, by J. Sovich; #90992 (1993).

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SOVICH, JERRY, ARCO Oil and Gas Company, Plano, TX

ABSTRACT: Prediction of Cobble Occurrence Using Electric Images

Production plans for Midway Sunset field in California include steam injection to develop the field. After recovering whole core, cobble zones and shale lenses were encountered which were not anticipated or forecast by the normal logging program. Concern was raised over reserve estimates and barriers to steam flooding.

A conductivity imaging tool was run over the cored interval in two wells to determine if the electric images could provide sufficient resolution to identify the cobble zones and thin shale lenses. Comparison to whole core showed that the electric images provided sufficient resolution to identify individual cobbles and sand matrix, as well as very thin shale lenses.

This conductivity contrast also was used to quantitatively measure and identify the presence of cobbles, sand matrix, shaly sand, and hard shales. The conductivity imaging tool samples the formation every 0.1 in. from 64 buttons distributed on four pads in contact with the borehole wall. Conductivity thresholds were picked to define the facies of interest (cobbles, matrix, shaly sand, and hard shales). Conductivities from each button falling within each category were counted and divided by the total number of samples to compute a percentage of each facies at each depth. The wells were divided into zones where necessary to account for changing rock conductivities. A computer program was written to automate the volume calculations and produce a continuous quantitative color display and isting.

Quantitative comparison using this technique to point count cobbles from core showed very good agreement. This technique is subject to the influences of mudcake, invasion, borehole washouts, and changing connate water resistivity, but it can still provide quantitative information. This method has also found applications in thin laminated sands to predict the amount of sand present and to differentiate rock type in complex lithologies.

AAPG Search and Discovery Article #90992©1993 AAPG Pacific Section Meeting, Long Beach, California, May 5-7, 1993.