Calculation method of variation function for predicting sandstone-type uranium ore bady by geostatistical inversion
WEI Da1, SUN Zhangqing2
1. E & D Research Institute, Liaohe Oilfield of CNPC, Panjin, Liaoning 124010, China; 2. College of Geoexploration Science and Techno-logy, Jilin University, Changchun, Jilin 130026, China
Abstract：The reliability of geostatistical inversion is mainly controlled by the selection of key parameters such as the variation function. The traditional method of calculating the transverse range of the variation function has high randomness. To improve the accuracy of geostatistical inversion in predicting sandstone-type uranium ore body, this paper proposed a method of calculating the variation function under the control of logging data and geological significance. In this method, the vertical range is calculated by counting the data points in the well. The transverse range is calculated through statistics and analysis of the ore body scales and ore-bearing properties of ore occurrences in a developed zone. Compared with conventional deterministic inversion, geostatistical inversion, based on random modeling of logging data, not only retains the high transverse resolution of seismic data but also displays higher vertical resolution. It has a good prediction effect in the Qianjiadian (QJD) sandstone-type uranium ore body with a small thickness and rapid transverse changes. Here, the calculation of the variation function is an important factor affecting the inversion result. The prediction accuracy analysis of the QJD uranium ore body and practical application in the study area conclude as follows:① When the vertical range is 4.5 m, the vertical resolution of the inversion result is the highest, and the inversion efficiency is high; ② Compared with post-stack sparse pulse inversion, the results of geostatistical inversion based on the proposed calculation method of the variation function are more consistent with the actual ore body distribution; ③ The discovery rate of industrial ore in 12 exploration wells deployed according to the inversion results obtained by the proposed method is 75%, and the average exploration success rate is greatly improved.
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