Blockchain in the Oil & Gas Supply Chain

This datafile tabulates ten examples of deploying Blockchain in the oil and gas industry from 2017 onwards; including the companies involved, the use cases, and our estimates of the cost savings.

Most prior examples have been in oil and gas trading, where cost savings tend to run at c35%. More niche applications are gaining traction in downstream, B2B applications.

For 2020, we are particularly excited by the broadening of Blockchain technologies into the procurement industry by a particular company, Data Gumbo.

c10% cost savings may be achieved for fragmented supply chains, such as US shale, by analogy to other digital procurement platforms we have evaluated in the past.

Super-Computers at Oil Majors?

This data-file tabulates super-computing capacity possessed by leading companies in the energy industry, based on public disclosures and internet sources: both directly owned by the companies, or available through partnerships with research institutions.

Computing capacity has increased by 70x since 2009, rising at a c50% CAGR. The pace of growth is quickening, with a 4x increase since 2016, which is a c60% CAGR.

Main usesfor the super-computers are in seismic processing, reservoir modelling and well-placement; but also for operational process efficiency and downstream catalyst development.

Leading companies are identified in the data-file, although this metric should not be over-emphasized. The largest reservoir simulation to-date was not conducted using an “owned” super-computer, but rather in partnership with an academic institution. The largest supercomputer in the world is also larger than the entire oil industry’s super-computing power combined.

ESP Optimisation Opportunities?

This data-file calculates the financial and carbon costs of running electric submersible pumps (ESPs) at oilfields, as a function of half-a-dozen input variables. This matters with ESPs fitted on 15-20% of the world’s c1M oil wells.

Opportunities to optimise: CO2 intensities can be lowered 25% by switching diesel-powered ESPs to natural gas, and theoretically by 100% by switching to renewables. Associated kg/boe and cost savings are tabulated in the data-file.

Leading Majors and new technology companies are also pioneering means to improve ESP efficiency. We tabulate our top examples in the data-file. Initiatives from Aramco and Equinor screen as most impressive.

Ventures for an Energy Transition?

This database tabulates c200 venture investments made by 8 of the leading Oil Majors, as the energy industry advances and transitions.

The largest portion of activity is still aimed at incubating Upstream technologies (c40% of the investments), as might be expected.

But leading Majors are also building rapid capabilities in new energies (38%) and digital (36%), as the energy system evolves. We are impressed by the opportunities. Venturing is likely the right model to create most value.

The full database shows which topic areas are most actively targeted by venturing; including by company. We also chart which companies have gained stakes in the most interesting start-ups.

The cutting edge of shale technology?

This data-file reviews 300 technical papers from 2018 and 350 technical papers from 2019. Hence, we can  identify the cutting edge of shale technology. Each paper is summarised, categorized by topic, by country, by basin, by company and by ‘impact’.

The YoY trends in 2019 show an incredible uptick in EOR, machine learning and well spacing studies, which are fully reviewed in the file.

On our assessment, one third of the papers support material improvements in well-productivity.  c98% are data-driven, including c39% using advanced computational modelling and another c20% using data to optimise operations.

The Permian hosted the most research, pulling further ahead of other basins. You may be surprised by the identities of the companies publishing the most technical papers in shale.

Well-by-well optimisation?

Production optimisation can uplift mature fields’ output by 5-20%, varying production rates, chokes, pump-rates and EOR strategies, well-by-well across a field.  It’s another way to stave off decline rates. But how?

This data-file summarises the methodology employed by BP, based on the most detailed patent we have seen on the topic, in our screen of 3,000 patents across the industry. BP is a leader in this area. Having digitised most of its operated assets, production optimisation comes next.

The typical challenge across the industry, is that as many as 20-30 changes may be required to optimise a large field, which is time-intensive for engineers to perform manually, hard-to-prioritise, hard-to-sequence and prone to errors that might defy operational constraints on individual wells.

BP’s system iterates through potential changes, selects the most promising candidates, validates that they comply with operating constraints, and shifts production to an optimal state (chart above).

This data-file includes our summary of BP’s patent, schematics for its implementation, data behind our chart above and a ranking of BP’s  “digital technology” versus other Majors that we have assessed.

 

Can super-computers lower decline rates?

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.

Johan Sverdrup: Don’t Decline

Equinor is deploying three world-class technologies to mitigate Johan Sverdrup’s decline rates, based on reviewing c115 of the company’s patents and dozens of technical papers. This 15-page note outlines how its efforts may unlock an incremental $3-5bn of value from the field, as production surprises to the upside.

Deploying the Digital Twin

This data-file tabulates 36 recent technical papers into “digital twins”, in order to understand how the technology is being deployed around the upstream oil and gas industry.

The data show the most common uses of digital twins, the most common context, the timing of the technology’s ascent and the companies who feature most prevalently in the technical literature.

Inflow Control: Our Top 20 Papers from 2019

This data-file summarises twenty recent papers using inflow control devices: an exciting digital technology to optimise horizontal wells by limiting production from zones that are susceptible to flowing water or gas.

To lower global decline-rates, adoption is increasingly widespread at horizontal wells around the conventional oil industry. Described operators include Aker-BP, CNOOC, Equinor, KOC, Lukoil, Mubadala, OMV, PetroChina, Rosneft, Aramco, Schlumberger, Suncor and pure-play Tendeka.

Each paper is categorized by company, by country, specific fields (if relevant), paper-type, focus, well-type, ICD-type, our assessed “impact” and a short summary.

Our “Top 10 facts” on ICDs are also summarised in the data-file…