“Taking ideas from the use of quantitative interpretation in conventional reservoirs, we construct a new workflow for the interpretation of unconventional reservoirs, that leads to a means of identifying potentially viable shale formations with high kerogen content, associated with high hydrocarbon content, from poorer formations.

Starting with the derivation of the total organic carbon (TOC) concentration from log and core data, which relates directly to kerogen content, the workflow uses the rock physics modelling of velocities and density to allow the shales to be parameterized in terms of separate kerogen and non-kerogen properties and uses forward modelled synthetics to understand AVO characteristics of the formations. With log data from two separate producing reservoirs, we use kerogen substitution to derive velocity and density data representative of high and low TOC concentrations, which we place into AI versus SI space to propose how simultaneous inversion might be used to map productive target zones.”


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