Application of Geological Modeling Technique Based on Seismic-Frequency-Extension-Processing and Geostatistical-Inversion in the Development of Extra-Heavy Oil Reservoir with Interlayers
Authors: Lv Zuobin , Wang Shuanglong , Geng Zhigang , Liu Hongzhou , Wang Cong , Lv Yuanzhe 
Published: February 2025

LD Oilfield is located in Bohai Bay Basin, China. Its sedimentary facies type is braided river deposit, which is an offshore extra-heavy oil reservoir. It is currently in the pre-drilling optimization stage of development plan,has seven drilled wells. Interlayers are well developed and the average thickness of interlayers is only 2∼3m. The reservoir is developed by thermal production. Low resolution of raw seismic data makes it difficult to identify interlayers, and the establishment of an accurate reservoir geological model is a great challenge.

In order to solve the above problems, in this study, an integrated geological modeling method based on seismic frequency extension processing and acoustic impedance geostatistical inversion is proposed.There are three key aspects to this method. Firstly, a high resolution sequence stratigraphic framework of the target intervals is established by using sequence stratigraphy and sedimentology. Secondly, frequency extension processing of seismic data is carried out. Based on the seismic data after frequency extension, acoustic impedance geostatistical inversion combining well logging and seismic data is carried out to quantitatively predict distribution of conglomerate interlayers. For thin mudstone interlayers which can not be identified after frequency extension, genetic inversion of shale content is carried out and reservoir prediction is made. Finally, due to the large differences in physical properties between different lithofacies, in order to accurately characterize the physical property distribution of different lithofacies, a nested hierarchical three-level lithofacies constraint modeling method is used to establish a fine lithofacies model, and 3D physical property models are established under the fine lithofacies model constraint by stochastic simulation.

The target intervals in LD Oilfield are the lower member of Neogene Minghuazhen Formation and Guantao Formation, which are vertically divided into 2 sequences and 9 sub-sequences.The lithology revealed by 7 wells is mainly sandstone, conglomerate and mudstone, and the latter two are interlayers. Based on drilling and logging data, the sensitivity analysis of rock elastic and physical parameters to lithologies is carried out by crossplot statistical analysis. The analysis results show that acoustic impedance can distinguish between conglomerate and non-conglomerate, and shale content can distinguish between sandstone and non-sandstone; the quantitative prediction of conglomerate interlayers is carried out by acoustic impedance geostatistical inversion, and the shale content inversion based on genetic algorithm is carried out to predict sandstone and non-sandstone well. On the basis of reservoir and interlayers prediction, the facies-in-facies modeling method with step-by-step constraint is adopted: the first-level lithofacies model is established according to geostatistical inversion results, and the second-level lithofacies model is established according to the constraint of shale content inversion results. The sandstone at the well points are further subdivided into fine, medium and coarse, and the third-level fine lithofacies model with 5 types of lithofacies is established. The 3D physical property model is established with the constraint of the fine lithofacies model, which provides a more accurate static model for the optimization of pre-drilling plans in the oilfield.

Based on the results of the study, during pre-drilling optimization, the location of nearly 1/3 of the development wells in the oilfield were optimized, 3 risk wells were eliminated. Optimized reservoir index is obviously better than that of ODP (short for overall development plan). This research method can be used for reference to similar oilfields.