Quantitative Interpretation of TOC in Complicated Lithology Based on Well Log Data: A Case of Majiagou Formation in the Eastern Ordos Basin, China

Source rock evaluation plays a key role in studies of hydrocarbon accumulation and resource potential. Total organic carbon (TOC) is the basis source it parameter that influences petroleum assessment. The Majiagou formation eastern Ordos Basin has complicated lithology low abundance matters. There are different opinions over existence scale rocks. Due to inadequate laboratory data TOC Basin, difficult accurately describe rocks region; thus, log interpretation needed. In this study, neural network model artificial intelligence (AI) field was introduced into logging interpretation. Compared with traditional ΔlogR methods, sample optimization, correlation analysis comparative optimization computational methods were carried out successively by using measured data. Results show good prediction effect lithologic regions can identify variations continuous strata regardless quick changes.