Page 248 - Intelligent Digital Oil And Gas Fields

198 Intelligent Digital Oil and Gas Fields

or recovery factor. In this chapter, we discuss the techniques applied for his-
tory matching the production data and an overview on coupling subsurface
and surface models.
This chapter introduces the engineering principles and technology con-
cepts of IAMod, and optimization and the use of the models for IAM. The
IAMod developments were introduced in the E&P industry in the early
2000s (Liao and Stein, 2002), combining subsurface models with surface
production facilities and networks. They are now becoming a standard
means of modeling entire oil and gas assets with the objective to optimize
existing facilities and to plan enhancements to production (wells and
facilities).
To date, many operators have developed their own IAMods (Toby, 2014
and references therein); however, the ultimate benefits of such models and
particularly their business-added value have not been fully realized. The
underlying reasons may stem from the inherent complexity of the state-of-
the-art IA models, which makes for challenging model calibration (history
matching) that leads to uncertainty in the models and their forecasts
(Maucec et al., 2011). Thus, there is an added challenge that is attributed
to the fact that the modern IAMods now integrate advanced uncertainty
and riskmanagement (URM)principles, which—particularlywhen deployed
in large-scale, full-field studies—require substantial computational resources
(Dzuyba et al., 2012; Maucec et al., 2017). While the integration of URM
concepts in IAM processes enhances their operational applicability and excel-
lence, it also adds to the challenge of quantitatively evaluating various devel-
opment and economic scenarios. Moreover, the integration of URM and
IAMod ultimately leads to integrated asset management—a decision-driven
reservoir optimization, which in open technical literature is interchangeably
(and sometimes confusingly) associated with the same acronym IAM.

6.1 INTRODUCTION TO IAM AND OPTIMIZATION

Before introducing the principles of IAMod and optimization, let us
look briefly at the notation and abbreviation patterns that one will encounter
in the open technical literature, for example, in the publications of the Soci-
ety of Petroleum Engineers (SPE).
In this work, the integrated asset model or modeling is “IAMod,” while
integrated asset management is “IAM”. This notation is incorporated in
Fig. 6.1, which outlines the framework for a holistic IAM. The reservoir