A Method To Normalize Log Data by Calibration to Large-Scale Data Trends

摘要

Wireline log data is subject to numerous potential errors duernto the acquisition environment and assumptions made duringrnacquisition. The literature sites log quality problems on thernorder of fifty percent of all well logs. The implication of thisrnis that wireline log normalization is a critical step in obtainingrnmeaningful log data for any reservoir characterization orrnmodeling study. Often insufficient information is available tornproperly normalize logs using common or traditional methods.rnA new method is introduced in this paper that relies only on arnsufficiently thick log interval to properly estimate thernparameters needed for the normalization. Through the use ofrnfirst vertical averaging of data by well to minimize localizedrnreservoir variations, followed by areal averaging of multiplernwells to estimate correction terms for tool calibration affects, arnrobust method of well log normalization is presented. Anrnexample using data from the Fullerton Clear Fork Field isrnpresented to illustrate the method.