Experience in seismic facies analysis application during prospecting and exploration

   Issues of practical application of the results of seismic facies analysis are of concern to subsoil users and specialists from scientific institutes in the oil and gas industry. It is not always evident what contribution this work makes to the outcome of geological modeling and what significance it has when integrating materials from areal seismic studies, geophysical well surveys andcore data. At the same time, interest in this type of work decreases as fields are drilled, although with increasing well data, the reliability of the results of seismic facies analysis increases significantly, and additional opportunities arise to search for promising and undeveloped zones of the deposit.   In this regard, the main objective of the article is to remind the public of the importance of this component of geological modeling, to illustrate the practical applications of seismic facies analysis, and to present various approaches to seismic facies mapping.   The article describes approaches to seismic facies analysis at different stages of exploration of promising areas and fields, taking into account 2D and 3D seismic exploration. It is noted that the use of neural networks for calculating seismic classes makes it possible to work with different input data, including volumetric cubes of digital material and two-dimensional maps constructed from the results of seismic exploration. Attention is a paid to the role of seismic facies analysis in creating geological models and assessing the resource base. An option is a shown for calculating a three-dimensional cube of lithology and reservoir properties taking into account seismic facies analysis and lithofacies analysis with a brief description of modeling algorithms. The impact of seismic facies analysis and lithofacies analysis results on the distribution of reservoirs within the three-dimensional geological model is illustrated through the example of the simulation area. Furthermore, the mapping of zones of probable claying of the productive formation is demonstrated.

seismic facies analysis, seismic class, seismic attribute, dynamic analysis, neural networks, geological model