Abstract

A multiwell study integrating mineralogy from core samples’ X-ray diffraction (XRD), standard openhole logs, and capture spectroscopy logging measurements was undertaken to understand differences between the log and core seen predominantly in anhydrite intervals. Determination of accurate lithology is important in oil and gas reservoirs because mineralogy affects the accurate determination of porosity, producibility, and reserve estimates.

The formation consists of calcite (limestone), dolomite, and anhydrite, which are common in many carbonate reservoirs around the world. Small amounts of pyrite, other sulfides, clay, and quartz are also found. Analysis of this complex mineralogy is further hampered by environmental complications that include high borehole and formation temperatures and heavy barite-weighted mud, which results in the photoelectric factor (PEF) not being a reliable measurement.

In this case study, a positive bias in the log-derived anhydrite volume was observed in tighter, nonproductive carbonate sections. As the anhydrite volume is determined directly from the capture spectroscopy sulphur measurement, this bias suggested a potential problem with the measurement. As the bias was small (0 to 3 weight percent) and the anhydrite distribution in the rock is very heterogeneous, the determination of the cause of this apparent problem was difficult.

A number of different potential causes of the bias were reviewed to determine if they adversely affected log-derived lithology. Capture spectroscopy data acquired at faster logging speeds demonstrated the bias at small volumes of anhydrite; the bias disappeared in zones with significant amounts of anhydrite. In addition, mineralogy and elemental analysis from veneer slabs improved the quantification of the sulphur and consequently, the anhydrite content of the formation, enabling accurate determination of anhydrite volumes, even in the heterogeneous sections. Proper averaging techniques of the core data with log data also verified the sulphur bias at low anhydrite levels. The results of this study confirmed that the apparent sulphur bias was the result of statistical precision. Improvements to the log data require slower logging speeds, modifications to data acquisition, processing, and better wellsite log quality control.

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