Abstract: The prediction of sweet spots in shale oil reservoirs is affected by many factors. Clarifying the main controlling factors and assigning reasonable weights is the key to fast and efficient sweet spot evaluation. The traditional prediction method of shale oil sweet spots is not reasonable in terms of weight and classification standard. For this reason, firstly, the grey correlation analysis method is used to analyze the main control factors; then, the multiple correlation coefficient method is used to reasonably assign the optimal main control factors according to the type of reservoir to which they belong; finally, the geological engineering sweet spot coefficient of the reservoir is established to realize accurate prediction of shale reservoir sweet spots. Taking the Chang 7 shale oil reservoir in Longdong Aera of Changqing Oilfield as the research object, by using logging data, 10 representative geological and engineering parameters are selected from the aspects of source rock property quality(SQ), reservoir physical property quality(RQ) and completion quality(CQ) and the geological engineering double sweet spot eva-luation standard of shale oil reservoir in the work area is established: X_SQ>0.581, X_RQ>0.494 and X_CQ>0.715. The sweet spots predicted by this standard are in good agreement with the actual high and low production areas, which confirms the accuracy of the method. The research can provide a theoretical basis for the sweet spot prediction and well location layout of the Chang 7 shale oil reservoir in Longdong area.

Key words: logging data, sweet spot prediction, main controlling factors, grey correlation analysis, evaluation standard