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Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data Driven Models by Keith Holdaway

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Chapter 6Reservoir Management

Knowledge makes you free from the chains of ignorance, and revives your heart; knowledge takes you out from the darkness of suspicions and superstitions, and gives a new light to your eyes.

Hazrat Abu Ali Saqfi

The goal of reservoir management is to maximize the economic profitability or net present value of the asset (hydrocarbon reserves) while minimizing CAPEX and OPEX.1 Controlling operations to maximize both short- and long-term production predicates a lifecycle optimization based on reservoir model uncertainties together with model updating by production measurements, time-lapse seismic, and other available data. Time-lapse seismic data, for example, help to determine reservoir changes that occur over time and can be used as a new dimension in history matching since they contain information about fluid movement and pressure changes between and beyond the well. How can we process and use the huge amount of information in an efficient way and ensure that the reservoir models are kept up to date and consistent with the data? We shall explore some of the data and associated analytical methodologies appropriate to reservoir management in the case studies.

Reservoir management tasks can broadly fall into one of four buckets:2

  1. Classification
  2. Estimation
  3. Segmentation
  4. Description

The classification task essentially puts labels on everything deemed important for a study. Thus, to identify ideal well candidates for a stimulation workflow, we could ...

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