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.
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.
There is only one way to decarbonise the energy system: leading companies must find economic opportunities in better technologies. No other route can source sufficient capital to re-shape such a vast industry that spends c$2trn per annum. We outline seven game-changing opportunities. Leading energy Majors are already pursuing them in their portfolios, patents and venturing. Others must follow suit.
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.
The appetite to invest in new offshore oil projects has been languishing, due to fears over the energy transition, a preference for share-buybacks, and intensifying competition from short-cycle shale. So can technology revive offshore and deep-water? This note outlines our ‘top twenty’ opportunities. They can double deep-water NPVs, add c4-5% to IRRs and improve oil price break-evens by $15-20/bbl.
This data-file quantifies the impact that technology can have on offshore economics. We start with a 250-line field model, for a typical offshore oil and gas project. We then list our “top twenty” offshore technologies, which can improve the economics. In a third tab, we update our base case model, line-by-line, to reflect these twenty technologies. Finally, the “before” and the “after” are compared and contrasted.
We have modelled the economic uplift of extra digital instrumentation on a typical Permian well. If the data can uplift production by 2.5%, then c$0.4M of instrumentation costs would “pay back” (i.e., break even). If the data can uplift production by 10%, it would add +$1M of NPV and +5% IRR per well. These numbers are all shown at $50/bbl, but you can flex the inputs in our model.
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.
