ESTIMATING LITHOLOGIC COMPOSITIONS FROM DIGITAL MUD LOGS ACROSS THE NORTH SLOPE OF ALASKA

HAYBA, Daniel O. and BURNS, W. Matthew, U.S. Geological Survey, MS 956 National Center, Reston, VA 20192, [email protected]

Determining lithologies from wireline logs can be equivocal, especially when using older (analog) and often limited suites of logs. It is common practice to use lithologies determined from mud logs to help guide and reduce uncertainties in this process, but results are largely qualitative. Improvements are hampered by the fact that most mud logs are not digital and that it is cumbersome and time consuming to convert paper logs into usable digital form. We developed a macro-based spreadsheet application, named Lithos, that facilitates (but does not fully automate) this process. Utilizing this approach, we have digitized the mud logs for more than 30 wells across the North Slope of Alaska. Digital lithologic logs were also prepared using Lithos to convert text (ASCII) descriptions of down-hole lithologies into comparable digital form for nearly 30 additional wells.

Because mud log data is compromised to varying degrees by physical averaging and caving, a stratigraphic unit approach was used to analyze this digital lithologic data. At this scale (for units at least 250 ft thick), we assume that in each well the lithologic proportions derived from the mud logs are representative of the unit as a whole. These portions then help scale the criteria applied to determine lithologies derived from the wireline logs, so that their overall lithologic proportions generally agree to within about 10% of those determined from the digital mud logs. We employed this approach for exploratory wells widely distributed across much of the North Slope. In each well, the amount of coal in each stratigraphic unit was determined along with the relative proportions of sandstone, siltstone, shale, limestone, and dolomite. These results are displayed in map form by contouring the significant lithologic proportions. The effectiveness of this approach was verified against lithologies estimated solely from electric logs, which frequently overestimated the amount of coal. The "ground truth" that digital mud logs provide in augmenting wireline-derived lithologies is important to applications that require accurate lithologic estimates, such as quantitative modeling of basin evolution, including compaction, thermal maturation, and hydrocarbon generation.