Placement of the horizontal well within the best landing zone is critical to maximize well productivity; thus, identification of the best landing zone is important. This paper illustrated an integrated semianalytical workflow to carry out the stratigraphic characterization of the Eagle Ford shale to identify the best landing zone. The objective of this work is twofold: (1) to establish a workflow for stratigraphic characterization and (2) to understand the local level variability in the well performance. To establish the workflow, we have used the production data, petrophysical information, and regional reservoir property maps. As a first step of the workflow, we subdivided the Eagle Ford shale into nine smaller stratigraphic units using the wireline signatures and outcrop study. In the second step, we have used statistical methods such as linear regression, fuzzy groups, and theory of granularity to capture the relationship between the geologic parameters and the well performances. In this step, we identified volume of clay (Vclay), hydrocarbon filled porosity (HCFP), and total organic carbon (TOC) as key drivers of the well performance. In the third step, we characterized the nine smaller units and identified four stratigraphic units as good reservoirs with two being the best due to their low Vclay: high HCFP and high TOC content. Finally, we reviewed the well paths of four horizontal wells with respect to the best stratigraphic units. We observed that the production behavior of these wells was possibly driven by their lateral placement. The better producing wells were placed within the middle of the best stratigraphic units, whereas the poor wells were going out the best stratigraphic units. This investigation provided a case study that demonstrated the importance of integrating data sets to identify best landing zones, and the suggested workflow could be applied to other areas and reservoirs to better identify targetable zones.

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