油ガス田開発における探鉱リスクと資源量評価手法

－確率論的地質モデル構築に向けた挑戦と その解決，ワークフローに関する検討

抄録

This paper will focus on the development in assessment methodology over the last decades, why the industry is updating their methodology, and the added value this gives the assessors and the decision makers. Improved resolution in prospect definition, from 2D to 3D seismic data, yielded multiple reservoir prospects, which necessitated an update of the risk and resource assessment methodology. In most cases, detailed prospect models with separate closures and reservoirs will have multiple success scenarios. For correct statistical modelling, risk and volume dependencies as well as possible fluid communications between the reservoirs must be honoured.

When 2D seismic data dominated in exploration, resolution was low, and most prospects were modelled as single containers. The increased use of 3D seismic data in exploration resulted in subsurface resolution improvements with multiple compartments and multiple reservoir prospects. Therefore, prospect assessment methods must evolve and enable us to create correct probabilistic representations of such detailed geo-models. Today, the objective of prospect assessment is not only to model the overall chance of success （COS）. It is also critical to model the COS of the different success scenarios and the volume distributions, given that all reservoirs/compartments are tested. To capture all prospect success scenarios in a probabilistic model, it is imperative to handle parameter correlations, risk dependencies, and potential ?uid communications between the different reservoir units/compartments in a prospect. The objective is to enable geoscientists to recreate their understanding of the uncertainty, risk, and possible success case scenarios of prospects in a stochastic model. The established industry best practise for prospect assessment is a four-step process:

A） First, defined the possible success and failure combinations of the prospect, given that all reservoirs/compartments are tested.

B） Break the prospect down into individual reservoirs/compartments that can succeed/fail independently; these are assessed individually with respect to risk and volume.

C） Enrol the assessed reservoirs/compartments into a prospect where risk dependency and possible fluid communication are modelled.

D） Sort success trials from the prospect simulation into groups representing the different possible success scenarios identified in the prospect description.This article will show four different assessments of a multicompartment prospect to illustrate the differences in results going from a simplistic to a geologically realistic assessment.

In addition to geologically realistic assessments of the individual prospects, consistent and comparable analysis is a prerequisite for building and maintaining an exploration portfolio that delivers the predicted results. The last part of this paper will discuss how pre- and post-well analysis and portfolio performance tracking can be used as tools to improve and maintain the exploration performance.