The Application of the Geostatistical Inversion in Shale Lithofacies Prediction

Abstract

Abstract

The spatial heterogeneity of shale lithofacies has an important influence on the enrichment and preservation of shale gas. However, there is no valid method for the spatial distribution prediction of shale lithofacies. The geostatistical inversion combines Markov chain, Monte Carlo simulation with the inversion based on models and owns the advantages for the lateral continuity of seismic data and the vertical high resolution of log data, making it possible to predict the distribution of shale lithofacies.

Fuling Jiaoshiba shale gas field in China made a great breakthrough on the shale gas exploration and development. In this study, based on 3D seismic data, drilling and core data of the Jiaoshiba area, we try to predict the shale lithofacies distribution of the Upper Ordovician Wufeng Formation to the Lower Silurian Longmaxi Formation using the geostatistical inversion.

Firstly, based on the XRD results, four lithofacies are recognized: siliceous shale, clay shale, calcareous shale and mixed shale. After that, drilling, logging and seismic data are combined to establish the high-precision isochronal formation frame. Different geophysical methods, including constrained sparse spike inversion and the geostatistical inversion, are used to predict the shale lithofacies spatial distribution. The results show that the siliceous shale is mainly developed in the Wufeng Formation to the lower stratum of the Longmaxi Formation and it is widely and stably distributed in the study area, while the calcareous shale is fragmentarily distributed. The mixed shale is mainly developed in the middle stratum of the Longmaxi Formation, while the siliceous shale has a banding distribution and its content reduces. In the upper stratum of the Longmaxi Formation, the clay shale is mainly developed in the study area and spreads widely as patchy in spatial distribution, while the development scale of the mixed shale is decreased.

The vertical resolution of lithofacies forecast result could be 1-2m in this study, and the validity of the result has been proved by the drilling wells. According to the research, the geostatistical inversion can effectively solve the problem of high resolution lithofacies identification and spatial distribution predicting in shale gas reservoir in the Fuling Jiaoshiba area. The methods and result can provide some references for the study of shale lithofacies in other areas with similar background.

AAPG Datapages/Search and Discovery Article #90260 © 2016 AAPG/SEG International Conference & Exhibition, Cancun, Mexico, September 6-9, 2016