Integrated workflow or method for petrophysical rock typing in carbonates

Abstract

Disclosed are various embodiments of a workflow or method for petrophysical rock typing of carbonates in an oil or gas reservoir or field comprising determining a Data Scenario (DS) for the reservoir or field, determining a plurality of Depositional Rock Types (DRTs) for the reservoir or field, determining a Digenetic Modification (DM) from a plurality of diagenetic modifiers or primary textures associated with the plurality of DRTs, selecting a Reservoir Type (RT) corresponding to the plurality of DRTs,determining at least one pore type, and determining, on the basis of the plurality of DRTs, the Diagenetic Modification (DM), and the at least one pore type, a plurality of Petrophysical Rock Types (PRTs) associated with the RT.

Description

technical field [0001] Various embodiments disclosed herein relate to the field of petrophysical rock type determination and methods and systems associated therewith. Background technique [0002] Many of the world's known oil and gas reserves are found in carbonate formations. To optimize production from these deposits, petroleum engineers try to understand the physical properties of these formations, including their porosity and permeability. For many geological formations, the physical properties are primarily determined at the time of deposition and are modified to some extent by pressure and heat. It is thus possible to describe and classify such geological formations in terms of their depositional environment with some acknowledgment of subsequent changes in their physical properties. [0003] But carbonates present an unusual challenge because their properties can be greatly modified through the process of diagenesis, and rock types can be radically changed. Specif...

AI Technical Summary

Problems solved by technology

However, there are major gaps in existing methods in the following aspects: (1) incorporating diagenetic processes; (2) considering multimodal pore-throat distribution in pore sizing; (3) considering fractures; (4) integrating dynamic data; (5) Consider different scales; and (6) provide appropriate geostatistical tools to properly distribute PRTs in statistical reservoir models

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