Gamma-clustering Sequence Stratigraphy, Case Study of the Carbonate Sarvak Formation, Southwest Iran

Comprehensive study of seismic, well-logs and core data is essential in sequence stratigraphic analysis. In the absence of seismic and core data, gamma-ray logging is an important stratigraphic tool due to its sensitivity to shale content of strata. In this paper, gamma-ray log data are divided into two clusters. One cluster with higher average of gamma value is interpreted as being due to deeper sedimentary environments. A second cluster with lower average is due to shallower sedimentary environments or shelf deposits. This kind of interpretation is based on two assumptions: (1) a deeper depositional environment produces higher gamma emission, and (2) the gamma-ray log is not much affected from diagenetic processes. At each sampling depth, a positive label is assigned to the cluster with higher, and a negative label to the cluster with lower average. A cumulative diagram of the cluster labels was compared to previously studied environmental facies. It was illustrated that the diagram recreates the relative water depth change, so it identifies sequence surfaces (sequence boundary and maximum flooding surface). The identified sequence surfaces were compared to core-based sequence stratigraphy of the carbonate Sarvak Formation, southwest Iran, in two oil wells. Sequence stratigraphy interpretations are judgmental, i.e., based on expert opinion, and being judgmental is a source of uncertainty for further decision making. This work reveals that stacking patterns and system tracts of the third-order sequences in the carbonate reservoirs could be identified in a systematic way using gamma-clustering algorithm. Nevertheless, the well-log resolution is a limiting factor for identifying the fourth-order sequences.