In 2019, the virtues of switching diesel-powered frac fleets to gas-powered electric have been extolled by companies such as EOG, Shell, Baker Hughes, Halliburton, Evolution and US Well Services.
The chief benefit is a material cost saving, quantified per well in this file, as a function of the frac fleet size, its upgrade costs, its fuel usage. diesel prices and gas prices.
Additional benefitsare also noted in the file, such as CO2 reductions, higher reliability, smaller pad sizes, NOX reductions and noise reductions. We also think over the long run, 200mmcfd of stranded Permian gas could be absorbed.
This data-file summarises 25 of the most recent technical papers around the industry, using fiber-optic cables for Distributed Acoustic Sensing (DAS). The technology is hitting critical mass to spur shale productivity upwards.
For each study, our data-file tabulates the company involved, the country of application, the specific purpose and a short summary of findings.
Technical data are also tabulated from some of these papers, including for warm-back analysis, perforation design and cluster flow-allocations.
China’s future gas production, and thus its need for LNG imports, depends heavily on its prospects in shale: Technically recoverable resources have been assessed at a vast 31.6TCM by the EIA.
But >50% shortfalls are looming against the 2016 target to produce 30bcm by 2020. Production ran at just 11bcm last year. And many Majors have now exited. So what are the main challenges, hindering development?
In order to answer this question, we have summarised ten recent technical paper on the Chinese shale gas industry.
This data-file tabulates the most-cited challenges, and the solutions that are suggested to combat them. It also includes our “top ten conclusions” on Chinese shale gas.
We still hear critics of the shale industrydownplaying its productivity gains. Often, they are dismissed as a function of rising proppant intensity. We disagree. Enormous improvements are visible if you study the technical literature.
Hence, this simple data-file compiles fifty examplesof genuine productivity gains across the shale industry since 2015. A “one line” summary is provided for each improvement. We also believe each improvement will see further optimisation ahead.
We are happy to discuss these improvements in more details with you…
This database tabulates c200 venture investmentsmade by 8 of the leading Oil Majors, as the energy industry advances and transitions.
The largest portionof activity is still aimed at incubating Upstream technologies (c40% of the investments), as might be expected.
But leading Majors are also building rapid capabilitiesin 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 databaseshows 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.
This data-file decomposes the drivers of shale productivity in Alberta’s Duvernay play, across a correlation-matrix of 23 different variables.
Machine learning can be used to predict 78% of the variance in wells’ performance from this data-set, surpassing the 19-67% predictive power of regression models (chart above). Accordingly, $1M/well savings are suggested, while well productivity can improve by 19-97%.
Shale is a data industry. “Big data” approaches are the only way to capture the complex inter-correlations within shale’s productivity drivers. As shown below, well EURs are meaningfully correlated with 12 variables. The “largest” driver is “proppant placed”, which is itself meaningfully correlated with 16 other variables.
Machine learningis still in its infancy in the shale patch, representing c2% of total industry-research. It presents material upside.
This model assesses the economics of a shale-EOR huff’n’puff project. NPVs and IRRs can be stress-tested as a function of oil prices, gas prices, production-profiles, EUR uplifts and capex costs. Our input assumptions are derived from technical papers. We think that economics are increasingly exciting, as the technology is de-risked. As more gas is stranded in key shale basins, base case IRRs rise from c15% well-level IRRs to c20%.