1.2 Reservoir study = data and knowledge integration

The goal of an exploration or development asset team is to characterize the dimension, the rock properties and the fluid distribution of the reservoir that they are studying. This knowledge will be a key factor for their company to decide what to do next with its asset. The company might push the exploration further or start its development. On the opposite, the company might drop the area in case the resource is proven to be uneconomical to produce.

To define the dimension of the reservoir, the team must understand the geometry of the horizons and the faults (if any) delimiting the play as well as the depth of the different fluid contacts (oil-water contact, gas-oil contact…). The rock properties of interest will be those controlling the amount of hydrocarbons in the reservoir (facies, porosity, fluid saturations…) as well as those controlling how the rock and the fluids will behave once engineers start production (permeability, geomechanical properties…).

Reservoirs being deep underground, they are hard to describe. To characterize its asset, the team has to integrate all the possible data available. Well data will provide a lot of details near the wellbores (logs, core, cuttings, image logs, well testing…). Seismic data will complete this by giving a general image of the full reservoir, but with a limited level of resolution. At last, the team’s knowledge about geological concepts (depositional environment, basin evolution…) and engineering concepts (fluid mechanics, geomechanics…) will help organizing these different data together to characterize the reservoir as best as possible.
Data and knowledge integration has been at the core of reservoir characterization long before reservoir modeling started to be developed in the 80s. The concept is for example explained in domains such as geological mapping (Tearpock and Bischke, 2003) or geophysical interpretation (Lines and Newrick, 2004). Geomodeling didn’t “invent” data and knowledge integration, but it gives a new set of tools to push it beyond what was done previously.

Table of contents

Introduction

Chapter 1 - Overview of the Geomodeling Workflow

Chapter 2 - Geostatistics

Chapter 3 - Geologists and Geomodeling

Chapter 4 - Petrophysicists and Geomodeling

Chapter 5 - Geophysicists and Geomodeling

Chapter 6 - Reservoir Engineers and Geomodeling

Chapter 7 - Reserve Engineers and Geomodeling

Chapter 8 - to be published in the summer 2019

To be published mid-March 2018

Chapter 9 - to be published in the summer 2019

To be published mid-March 2018

References

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