It is becoming increasingly important to quantify accurately the economic risk associated with hydrocarbon development
projects. In particular, the marginal fields in the North Sea require optimal use of all available information to assess the associated economic risks. These data need to be combined in a formally unbiased way that honours the information content inherent in the data. Statistical theory provides the formal framework in which the 'Uncertainty' can be 'Managed'. PUNQ is aimed at further developing a methodology to quantify and reduce the uncertainty in production forecasts obtained from computer simulations of hydrocarbon reservoir models.
Reservoir simulation models are generally conditioned directly to static information obtained from well logs, and indirectly to the reservoir's observed historical dynamic performance
such as well pressures, water-gas ratios, etc. PUNQ follows a Bayesian framework in which the unknown reservoir parameters, expected to have a first order effect on predicted
performance, have to be estimated using a priori information on these parameters, and using an inversion process routinely referred to as History Matching (HM). Geologists and
reservoir engineers integrate their respective views at an
early stage by jointly selecting the HM-parameters, and by
defining a priori probability density functions (PDF) of these parameters. A likelihood function, or HM-response surface, is then constructed, describing the probability density that a
given parameter combination can reproduce the observed
The main technical objectives of the project are as follows: - development of techniques for mapping HM-response surfaces in the multi-parameter space;
- development of techniques for projecting HM-response
surfaces to forecasting uncertainty;
- evaluation of the value of underlying parameters for HM & quantification of forecasting uncertainty;
- efficient optimization of noisy objective functions;
- the development of efficient Fast Simulators.
Expected Achievements and Exploitation
The main challenges addressed in this project comprise
quantitative geological definition, flow simulation and
statistical formalism including optimization and search
techniques. The main deliverables are:
- an algorithm to compute the PDF of future production;
- method validation through a geologically (near)-realistic, heterogeneous synthetic case.
An objective of the PUNQ project is to pave the way for future exploitation of the method. Statistical theory and
optimization theory are becoming just adequate to allow the
development of formalisms capable of modelling the
uncertainties associated with hydrocarbon field development.
Funding SchemeCSC - Cost-sharing contracts
W5 1XL London
SW1E 6NN London
SW7 2BP London
2600 GA Delft
L69 3BX Liverpool