Quality Control/Quality Assurance Assessments of Core Analysis Data from Multiple Commercial Laboratories

Abstract

Abstract Hydrocarbon in place calculations and recovery predictions require data from a variety of sources. Of these sources, core data are, potentially, the most accurate because they are direct measurements. Therefore, reliable and representative core analysis data are essential to calibrate and validate tool-acquired data, especially, wireline logs. Special core analysis (SCAL) vendor laboratories are the primary sources or supplemental resources for the measurements and acquisition of core data. These laboratories are set up for more rapid throughput of large quantities of samples at costs lower than those of an oil company's internal laboratory. But very poor quality data can be generated by some vendors. This paper discusses Quality Control/Quality Assurance analysis and assessments of SCAL data from four laboratories. The multi-vendor SCAL program was formulated to evaluate specific petrophysical properties capabilities of the selected laboratories. The tests included porosity and permeability at varying stress, formation water resistivity (Rw), electrical properties (m and n), and capillary pressure by the centrifuge and mercury intrusion methods. Core plugs from two different formations were used in the evaluation. One set consisted of limestone plugs and the other set included sandstone samples. Baseline porosity and air permeability measurements and CT scans were used to screen the samples and divide them into subsets for the individual vendors. The only information provided to the vendors was plug designation. Some laboratories provided very poor quality data on some of the tests. They reported wrong results for porosity at varying stress, electrical properties, and mercury capillary pressure. Probe maintenance, contamination, and calibration were given as possible reasons for erroneous brine resistivity. Wrong saturation exponent values were attributed to saturation instability. The errors identified in this study can have significant economic impact on a field development program. Therefore, it is important that we exercise very strict supervision of the program and engage with the vendor throughout the data acquisition program. The QC/QA analysis used in this study can improve the performance of these vendors and the quality of data.