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To improve the prediction of thin reservoirs with special geophysical responses, a geostatistical inversion technique is proposed based on an in-depth analysis of the theory of geostatistical inversion. This technique is based on the Markov chain Monte Carlo algorithm, to which we added the contents of facies-constrained. The feasibility of the technique and the reliability of the prediction results are demonstrated by a prediction of the sand bodies in the braided river channel bars in the Xiazijie Oilfield in the Junggar Basin. Based on the MCMC algorithm, the results show that leveraging the lateral changes in the seismic waveforms as geologically relevant information to drive the construction of the variogram and the optimization of the statistical sampling can largely overcome the obstacle that prevents traditional geostatistical inversions from accurately delineating the sedimentary characteristics; thereby, the proposed algorithm truly achieves facies-constrained geostatistical inversion. The case study of the Xiazijie Oilfield showed the feasibility and reliability of this technology. The prediction accuracy of the FCMCMC algorithm-based geostatistical inversion is as high as 6 m for thin interbedded reservoirs, and the coincidence rate between the prediction results and the well log data is more than 85%, which confirms the reliability of the technique. The demonstrated performance of the proposed technique provides a preliminary reference for the prediction of the thin interbedded reservoirs formed in terrestrial sedimentary basins and characterized by small thicknesses and rapid lateral changes with special geophysical responses. [ABSTRACT FROM AUTHOR]

On the basis of high-resolution sequence stratigraphy, this paper establishes a sequence stratigraphic frame, and predicts reservoirs by analyzing velocity field, seismic inversion, and seismic attributes. In the case study of the Jurassic Toutunhe Formation braided river delta reservoir of Shinan 21 well block, middle of the Junggar Basin, space variant velocity field inversion and reservoir prediction were carried out based on the sequence stratigraphic frame and the reservoir prediction accuracy was improved. Comparing the prediction results with the real drilling shows that, when the burial depth of bed of interest is 2 500 m, the maximum prediction error of depth is only 10 m, and the average relative prediction error is 0.16%; for appraisal wells with an average effective sandstone of 13 m, the maximum prediction error of sandstone thickness is only 5 m. The structure mapping and reservoir prediction constrained by the sequence stratigraphic frame achieved success. Key words: sequence stratigraphic frame, reservoir prediction, Junggar Basin, braided river delta