Advanced reservoir modelling can stave off production declines at complex offshore assets. This data-file illustrates how, tabulating production estimates based on a technical paper published by Eni, an industry leader in applying high-speed computing power in its upstream operations.
Specifically, the paper simulates an offshore field-cluster in a single, Integrated Asset Model that covers 31 wells, drilled into 3 reservoirs (each is modelled in detail, with a total of 1.9M reservoir cells), 34 pipes, 4 oil platforms and 3 delivery points. Each iteration of this model takes an average of 3.5-hours to run.
Production can be uplifted by 60% according to the simulation, both in terms of EUR and in terms of year 5-7 production rate. 9pp of the uplift is achieved by simple reservoir optimisation. Another 21pp of uplift is achieved by identifying the key bottleneck, and building a new separation & boosting platform to alleviate it. A further 29pp of uplift comes from optimising the development plan for the new platform.
Emerging digital technologies appear to be keeping LT oil-markets better supplied than many expect, with production upside for the industry’s technology-leaders.
Completing a shale well depends on over 40 variables. Each one can be optimised using data. It follows that next-generation data could deliver next-generation shale productivity.
This note focuses on the most exciting new data methodology we have seen across the entire shale space: distributed acoustic sensing (DAS) using fiber-optic cables. It has now reached critical mass.
DAS will have six transformational effects on the shale industry. Leading operators and service companies are also assessed.
Is Shale-EOR the next wave of unconventional upside? The topic jumped into the ‘Top 10’ most researched shale themes last year. Stranded in-basin gas will improve the economics. Production per well can rise by 1.5-2x. The theme could add 2.5Mbpd to YE25 output.
This data-file summarises progress using machine learning to maximise production from mature wells by detecting errors and optimising production. The algorithms are getting more accurate.
Methodology. First, we tabulate the accuracy of prior ML studies, touching on initiatives from Equinor, Conoco and Concho. Next, we focus in on an excellent, recent technical paper, achieving 5-10% production uplifts using machine learning to optimise 300 wells at the Bahrain oilfield.
Hence we constructed a simple model for digitising rod pumps: we estimate $100k of NPV can be created through instrumenting a typical rod pump well early in its life.
Global decline rates can be lowered by c100kbpd per annum for over a decade, using these improved algorithms.
Shale is a ‘tech’ industry. And the technology is improving at a remarkable pace. But Permian technology is improving faster than anywhere else. These are our conclusions after reviewing 300 technical papers from 2018. We address whether the Permian will therefore dominate future supply growth.
This data-file breaks down the production losses at a giant offshore oilfield, across five categories and ten sub-categories. They are addressable with digital oilfield technologies, as shown by our notes. Advanced algorithms such as BP’s Apex solution, are capable of reducing the losses — particularly in the largest categories. Halving them could increase output by c55kbpd.
