QUANTITATIVE PREDICTION OF ORGANIC COMPONENTS IN SHALE OIL RESERVOIRS USING AN IMPROVED ALOG R METHOD

摘要

The use of logging technology to evaluate the source rock can establish the quantitative relationship between the logging data and the source rock geochemical parameters and calculate the longitudinal continuous distribution of the geochemical parameters of the source rock. In this paper, we take the Paleogene shale oil reservoir in the Da- mintun Sag, Liaohe Oilfield, eastern China as an example. We first performed logging identification on shale oil reservoirs. Then, the organic component in the shale oil reservoir was quantitatively predicted using the improved Alog R method. The results show that, the shale oil logging response characteristics of the Damintun Sag are characterized by “three highs and one low”: high gamma, high resistance, high acoustic wave time diffeence, and low rock density. When using the improved Alog R method, the superposition coefficient K affect the accuracy of calculating the organic carbon content. With the change of K value from small to large, the accuracy of identifying the organic carbon content should first increase and then decrease, and the turning point from increasing to decreasing is the optimal superposition coefficient. The improved model can calculate the organic carbon content without the need for LOM and ATOC parameters and without the need to manually read baseline values. The calculated values of the various geochemical parameters using the improved model in the Damintun Sag are consistent with the measured values, indicating the reliability of this method.