Advanced Well Logging Interpretation for Reliable Electrotyping of Low-permeable and Low-resistivity Formation

The target formation of a brown oilfield in Western Siberia is composed of a shallowing-up succession represented by siltstones in its base gradually replaced by sandstones toward its top. Due to the absence of detailed rockand electrotyping, the siltstones, having much lower resistivity and permeability, were assigned to a water-bearing section. However, the following up well tests detected considerable oil inflow from them as well. This motivated current research aimed at developing a new methodology of rockand electrotyping of low-resistive, low-permeable clastic reservoirs. The methodology comprises detailed workflow for laboratory tests, rock typing by means of the alternative flow zone indicator (FZI), and, finally, transfer of core-derived rock types to well log electrotypes. The proposed application of the dimensionless FZI parameter, incorporating porosity and irreducible water saturation, appeared to be very effective for electrotyping of the formation, including low-resistive and low-permeable intervals. Since the intervals are characterized by a low correlation between permeability and porosity, applying the latter log for computing permeability results in unreliable calculation of the parameter and further incorrect electrotyping. In order to resolve this issue, the study suggests an effective alternative technique for calculating permeability as a multivariate parameter from other logs. Further, the research proposes a well log interpretation workflow that enables conversion of the defined rock types to electrotypes, maintaining the same classification principles for both core and well logs data. This ensures compatibility of the core and well log-derived classes. The petrophysical interpretation workflow is enhanced with machine learning algorithms for reconstructing lacking logs as well as extending the defined electrotypes to uninterpreted wells. The proposed approaches to rockand electrotyping allows detection of previously missed productive intervals and thus enables extend the lifetime of the brownfield.