Subsea Separation: the elusive history

This database covers all 14 subsea separation projects across the history of the oil industry, going back to the “dawn of subsea” in 1969.

For each example, we tabulate the asset, region, operator, water depth, process technology, Service company, start-up year, power rating, oil capacity, gas capacity, water capacity and some notes.

What is interesting about the data is how elusive the technology’s ascent has been. Two of our projects were cancelled. The largest were 2.3MW. Subsea Boosting and Compression has been 4x more prevalent (chart below).

This matters for the Mero pre-salt field where an unprecedented, giant, 6MW subsea-separation project is being pioneered, to handle high gas and CO2 cuts.

 

Pre-Salt Brazil: FPSO Tracker

This data-file tracks the construction progress of 30 FPSOs that are being deployed in the Brazilian pre-salt oil province. In each case, we quantify the vessel’s oil and gas handling capacity, development timing and recent news.

We also compare the FPSOs’ gas-handling capacity with regional pipeline capacity. There will only be room to monetize one-third of the pre-salt’s produced gas volumes by the mid-2020s. The rest  must be re-injected (chart below).

 

Mero: Economic Model

We have modeled the economics of the Mero oilfield (formerly known as Libra), using public disclosures and our own estimates.

Our model spans >250 lines of inputs and outputs, so you can flex key assumptions, such as oil prices, gas prices, production profiles and costs.

In particular, we have tested the impact of different gas bottleneck scenarios on the field’s ultimate value.

Lula: how much growth left?

This data-file tracks the Lula oilfield, well-by-well, FPSO-by-FPSO, aggregating data from over 100 production reports, which are published monthly by Brazil’s national hydrocarbon regulator.

Hence we have formulated “production forecasts” for each FPSO, and for the entire field; in 2H19 and in 1H20. This matters for oil markets; and for pre-salt producers, such as Petrobas, Shell and Galp.

Our outlook is for slowing growth, due to rising water- and gas-cuts, which are reviewed well-by-well. One FPSO is now definitively constrained by gas-handling capacity. Another is off-plateau due to maturity. Six Lula FPSOs are now negotiating water-cuts, as shown in the data-file.

1H19 production was lower than expected, at just 72% of total installed FPSO capacity. Our notes attribute the drivers, and contextualise the growth ahead.

Decline Rates: the consensus?

This data-file tabulates market expectations for global decline rates, both their magnitude and their drivers, based on our ongoing survey, linked here.

Global decline rates are expected to average 5.2% in 2020-25, based on the results we have tabulated so far.  However, the consensus is broad, with a standard deviation of 2%.

Future declines are expected to be lower than past decline rates, of 5.7%. Although the rise of shale is seen increasing global decline rates, this is apparently being outweighed by the rise of digital technologies and offshore innovations.  Hence modestly more participants see 2020-25 oil markets as over-supplied than under-supplied.

Please feel free to disagree, and register your own views. We will then send you a discount code to download this data-file free of charge.

Permian Pipeline Bottlenecks?

This data-file tracks c50 oil and gas pipelines in the Permian basin — their route, their capacity and their construction progress — in order to assess the severity of pipeline bottlenecks.

Our assessment is that the Permian’s oil bottleneck is currently moderate, while the gas bottleneck is severe.

Both will see new pipeline additions. Oil bottlenecks are thereby relieved, while gas bottlenecks remain more constrained.

It is interesting to consider how the bottleneck will impact completion activity among operators in the basin, and by extension, implied productivity data…

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.

 

Power Trains? Electric, diesel or hydrogen

This data-file compares diesel trains, electric trains and hydrogen trains, according to their energy consumption, carbon emissions and fuel costs. The data are presented apples-to-apples, per passenger mile, based on worked examples. Seven train routes are compared on 20 metrics overall.

Travelling by train should be 2-15x more fuel-efficient, and 3-20x less carbon intensive than travelling by car.

Electric trains are most efficient and cost-effective. The drawback is that electrifying tracks can cost c$1.4M/km. Nevertheless, we are most positive on the electrification opportunity around railways, particularly using next-generation combustion technologies.

The world’s first hydrogen trains launched in Germany in September-2018. To be cost-competitive with entry-level diesel trains requires c$12/kg hydrogen, $6/gallon diesel and a $50/ton carbon price.

Relative costs and economics can be compared by varying inputs in the file.

 

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.