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.

Johan Sverdrup: Economic Model

We have modelled the economics of Equinor’s Johan Sverdrup oilfield, using public disclosures and 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 decline rates and recovery factors on the field’s ultimate value.

Technology Leaders Get Bought?

This data-file looks back at the fate of technology-leaders, i.e., the companies that developed the top ten, most-impactful new oil technologies of the 1980s and 1990s.

Nine out of ten were bought by larger companies; the one exception being a largest Integrated Service company, which was therefore too large to be acquired.

Take-over premiums ranged from c3-32%, suggesting that ultimately shareholders are rewarded for investing in technology-leaders.

However, timing is unpredictable and long-dated. It took 5-20-years from the technologies’ invention to the inventors’ acquisition.

Electric cars slow the energy transition?

Electric Cars are being overtaken by new electric vehicles, which achieve c3x greater decarbonisation per unit of battery material. This metric matters if one believes that battery materials are a limiting factor in the energy transition. To illustrate our case, our new Excel-file models two scenarios…

In the first scenario, 400kg of battery materials can be used to produce 1 electric vehicle, which displaces 1 gasoline taxi. The calculations show that 28 bbls of oil-equivalent energy and 12T of CO2 emissions are avoided each year.

In the second scenario, 400kg of battery materials can be used to produce 120 electric scooters, which displace 2.5 gasoline taxis. The calculations show that 96bbls of oil-equivalent energy and 37T of CO2 emissions are avoided. I.e., the scooters achieve 3x more decarbonisation than the electric car.

Moreover,  our numbers above only assume that one-in-three scooter trips displaces a car-trip, while the other two-in-three are deemed to be “new demand”. Per mile travelled, the scooters achieve 9x more decarbonisation than putting the same 400kg of battery materials into the electric car.

Please download the data-file to interrogate our assumptions and stress-test your own scenarios. We argue the “electric revolution” goes beyond replacing today’s ground cars with electric ground cars. The opportunities are in new vehicle types.

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.

Scooter Wars?

E-scooters can re-shape urban mobility, eliminating 2Mbpd of oil demand by 2030, competing amidst the ascent of “electric vehicles” and re-shaping urban economies.  These implications follow from e-scooters having 25-50x higher energy efficiencies, higher convenience and c50% lower costs than gasoline vehicles, over short 1-2 mile journeys. Our 12-page note explores the consequences.

Energy Economics of e-Scooters

This data-file contains all our data on the energy economics of e-scooters, a transformational technology for urban mobility, where demand has exploded in 2018 and 2019. And for good reason. The data-file includes:

  • Our projections of the oil demand destroyed by scooters
  • Our projections of the electricity demand created by scooters
  • Number of US travel-trips using shared bikes and scooters from 2010-18
  • Scooter costs versus car and taxi costs per mile
  • Average ranges and battery sizes of incumbent scooter models
  • Relative energy economics of scooters versus gasoline cars and EVs
  • Relative time taken to charge scooters versus EVs using solar panels
  • The proportion of scooter trips that replace gasoline car trips in eight cities
  • Profiles of the top 4 e-scooter companies
  • A timeline of shared mobility from 1965 to 2018.

The download will also enable you to adjust the input assumptions, to test different scenarios.

Offshore Capex for Technology Leaders?

Technology leadership determines offshore capex. Specifically, this data-file measures a -88% correlation coefficient between different Major’s offshore patent filings in 2018 and their projects’ capex costs.

The details: We have tabulated the number of Offshore Patents filed in 2018, across 25 leading Majors, from our sample of 3,000 patents. We have also tabulated a dozen, recent, offshore greenfields operated by these companies, which were sanctioned in 2017-19. Investments from Aramco, BP, Equinor, Exxon, Petrobras, TOTAL and Shell are included.

The lowest-cost  projects are not “easy oil”. The most economical project in the entire sample, at $17M/kboed, has a complex gas cap with a risk of asphaltene precipitation.  Also in the ‘Top 5’ are an Arctic greenfield, an ultra-deepwater carbonate with unusually high-CO2 and an ultra-high pressure deep-water field. Economical development depends on leading technology.

To see the projects included in the analysis, please download the data-file…