With a critical shortage of personnel and an expertise gap predicted in the future, much reservoir and facies modelling work could be left to early and mid-career geologists. Additionally, efficiency in the reservoir modelling workflow will need to be achieved in order to satisfy increased demand for field development plans. Quality might suffer under these two conditions: less experienced geologists and improvements in time to knowledge.
Modify the existing facies modelling workflow to incorporate expertise (by codifying knowledge packaged into technology) and utilise analogues to improve the robustness of facies models by grounding them in geological reality.
A mid-career geologist was able to build two facies models validated against 100s of analogues in 20.5 hours by using Ava Clastics® analogue database and sedimentology software. In contrast, the same geologist was able to produce only one model in 52 hours using an alternative method.
Creating a representative facies model is often challenging, for several reasons: a lack of well data describing the reservoir, the scarcity of analogue data used to build a model or even limited experience in using the modelling algorithms to build the facies model. Most asset teams rely on the expertise of senior geologists with years of experience in a specific field to create realistic facies models. In some cases, the organisation may have an in-house reference database of rocktypes and geological analogues, but for many large and mid-size E&P operators, these databases are not robust or globally accessible, and in some cases they don’t exist.
In today’s environment of tighter budgets and breakeven development costs that are higher than the price per barrel, accounting for reservoir heterogeneity at the facies scale can help operators more reliably understand how the rock units contribute to production. This understanding gives valuable support to investment related decisions such as which assets to retain, which to farm out, and whether to delay development or provide input to the development plan itself.
If the price of oil remains in the $40-60/bbl range over the next three to five years, the pressure to re-evaluate asset portfolios will increase as oil companies seek opportunities to remain competitive. Organisations that opted to delay field development (expecting a market recovery sooner than 2020) will be faced with a new problem. In order to maintain acreage they will be required to meet their field development obligations which places enormous time-pressure on the asset teams responsible for evaluating reservoir potential and production scenarios.
With a critical shortage of personnel and an increasing expertise gap predicted in the future, much of the facies modelling work could be left to early and mid-career geologists. Additionally, efficiency in the reservoir modelling workflow will need to be achieved in order to satisfy demand for reservoir models. With these two conditions, less experienced geologists and productivity improvements in time-to-knowledge, the quality of reservoir models could suffer.
In the following study, we aimed to answer this primary question: Can the facies modelling workflow be improved in terms of efficiency while maintaining or improving quality to help operators prepare for a future of limited expertise?