Diagenesis and diagenetic stages prediction of Ed₂ reservoir in the west of Bozhong sag

Abstract

Diagenesis of clastic rock and hydrocarbon generating capacity are closely related with diagenetic stages. Based on diagenetic evolution, reservoir diagenetic stages prediction method is proposed through making a contrastive study of simulation results and test results using core measurement data. The essence of this method is illustrated and its effectiveness is demonstrated using Ed₂ clastic sandstones in the west of Bozhong sag, Bohai Bay Basin, China. Measurement of paleo temperature (T), vitrinite reflectivity (Ro%) and the proportion of smectite in illite/smectite interstratified minerals (I/S-S%) indicate that there are there types of diagenetic stages in the study area, including early diagenetic stage B, middle diagenetic stage A1 and middle diagenetic stage A2. When only considering T index for diagenetic stages prediction, the simulation results are more conservative than measured data with some situations, and the simulation result using Ro% for diagenetic prediction is less than measured data in some wells. When I/S-S% is used, the two situations above both exist. Because depth, temperature, time duration, pressure and some chemical variables can change synchronously or asynchronously, it is difficult to attribute with certainty the parameters that affect the apparent diagenetic stages evolution series. Diagenetic stage variations can be significantly different in different parts of one sedimentary basin. A synthetic indexes method considering T, Ro%, I/S-S% to predict its distribution, and the simulation result has proved that the reliability of the model has greatly improved.

Keywords

Diagenetic stages / Clastic sandstones / Bozhong sag / Diagenetic simulation / Overpressure / Synthetic indexes

Acknowledgements

This research work was funded by Major Projects of National Science and Technology “Large Oil and Gas Fields and CBM Development” (Grant No. 2016ZX05027-02-007), Major Projects of National Science and Technology “Large Oil and Gas Fields and CBM Development” (Grant No. 2016ZX05024-003-004) and the National Natural Science Foundation of China (Grant No. 41672119). Our grateful thanks are due to Shanghai Branch of CNOOC Ltd. for their help in providing geological data. Thanks are also due to reviewers for their constructive suggestions.

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