A missing skill?

Apart from the obvious, a healthy source rock or two, what do Mature Provinces (conventional ones like the North Sea, US onshore basins, many in SE Asia) have in common with current unconventional, shale oil/gas, ‘hot spots’?

Data, tonnes of it!

When I ask colleagues who are working today in a US onshore shale play how many wells they have to work with, the normal answer is ‘thousands’, mostly with logs, cuttings, petroleum samples etc. Much of this dating from the basin’s earlier conventional period….and in all sorts of different formats, media…

Similarly, if I look at what IHS Markit say about their Rushmore Shale Performance Review, I see it has data on drilling, completion and fraccing for ‘over 13,000 wells’.

And have a look at what the UK’s OGA says about the amount of data it holds for the UKCS.

My perception is that not many petro-technical folk yet know how to get real value out of such large data volumes and are often reduced to driving somewhat preconceived models through sub-sets of the available data.

Hence to my ‘missing skill’:

1. The ability to take data from any source and get it into a form that can be worked on, bearing in mind the specific objective.
2. To go beyond our conventional approach – which has been to put data on a map, generate a cross-plot, fit bi-variate least squares and so on – and apply modern Analytical techniques.
3. To pull out a solution which impacts a real business problem: for example, can an operator use Rushmore’s Drilling Performance Review which has details of ‘over 60,000’ wells to design ‘the optimum well’ for their location and target?

Some call the exponents of this skill Data Scientists. They are, I think, in short supply.

A sort of AI Quiz!

“Whydriverless cars might not hit the road so fast” is an article on LinkedIn by Scott Nyquist who is a Senior Partner at McKinsey & Company: we are both on the Advisory Board at Kimmeridge Energy LLC.

 

I guess you can only access it if you are registered on LinkedIn but basically he is predicting that the growth in autonomous vehicles (and electric cars too) might not go as fast as everybody is currently prognosing.

It reminded me of when I pitched up in Houston from Denver a couple of months ago. My flight was 3 hours late and by the time I got to the car rental car park there was one car left which thankfully turned out to be my Jeep automatic. But suppose the guy had said "Sir, there's just one car left and it's this autonomous vehicle!" Through my mind would have flashed – “find the Hardy Toll Road, do 610 West and then 610 South with an 18-wheeler either side, off at Woodway, sharp right, sharp left...."

Would I have said "That's great, thanks!" or "You know what, I'll just take the shuttle bus back to the Terminal and take a cab!"?

Straw poll of acquaintances is 100% the latter option.....

So here is the Quiz question: what would you have done???

Using AI to improve E&P performance

You may have noticed this news item a few weeks or so ago, talking about BP’s plans to introduce AI to seek drilling performance improvement.

It seems these plans are part of an effort to embrace new technologies, which Bob Dudley, BP’s chief executive, said last week were “rewriting the rule book for E&P”.

This set me thinking (again) about where are the E&P problems – the opportunities for performance improvement that could have such an effect?

I had a few ideas and here are some of them – not in order of importance but roughly in the order in which they occur in the value chain:

Using satellite- and air – borne sensors: there has been an explosion both in the number of vehicles flying around above us and in the bandwidth and resolution of the sensors they carry, Can we analyse these potentially huge data sets to reveal geological variation, map micro-seepage etc?  Make onshore exploration more successful……

Interpreting 3D and 4D seismic: huge data volumes - essentially we use such seismic to “do geology”. Geology is a rules-driven science; can a machine learn from previous interpretations and outcomes how to do this much better than humans?

Drilling: the point of the article about BP. Can a machine learn from the thousands of wells that have been drilled (in any one basin onshore USA; North Sea etc) how to optimise drilling performance? A useful performance metric is days/10k ft; is a focus on reducing Non Productive Time(NPT) the only key to performance improvement or are there others, for example the real-time adjustments that the BP article mentions?

Completions: again, from the thousands of wells drilled in any one basin or region, can a machine learn how to optimise/maximise IP (Initial Production)?

Preventative Maintenance: can we do as the airlines seem to do routinely and learn to predict equipment issues and failures before they actually happen? In turbines and compressors for example: I find it only slightly ironic that GE who sell such things are at the forefront of trying to sell software to tell us when they will break……

Actually, as a pointy-toed geoscientist I am underselling the impact that analytics could have on production operations, in fact on the whole of the engineering that that takes place between the well head and the storage facility. For a much better account, I refer you to Karl Jeffrey’s summary of a recent Finding Petroleum event on “Transforming offshore operations – with better use ofdata” which you can access by clicking on that title. There are so many things that could be done to improve efficiency, cut costs, prevent incidents, improve operational integrity, improve safety…….

"Winners" and "Losers" with a LFE* oil price

When discussing future oil prices, some CEOs seem to have moved on from ‘Lower for Even Longer’ to ‘Lower into the 2020’s’ to ‘Lower For Ever (*LFE)’.

Compared with the late 1990’s, this period of low oil prices has not yet seen a huge amount of consolidation – debt re-structuring, yes – but not outright acquisitions.

Exploration Performance in the 1990’s as a cause of ultimate demise!

It is said that banks and funds invest at least as much in the management teams of small exploration companies as in the actual prospects they are shown.

And therefore it is still common to read, in a company’s prospectus, that “X and Y were part of Z Oil’s widely respected and highly successful exploration team” or similar.

It is worth recalling that exploration is in general a game in which there are a few “winners” and very many “losers” and that in fact those that “lost” in exploration in the 1990’s were generally on the receiving end of consolidation at the end of the decade; this has been thoroughly documented by consultants such as ADL, Wood Mackenzie and others.

An example of these real differences in performance is shown in Figure 1 (a ‘classic’ exploration performance benchmarking display, showing reserves replacement as a percentage on the vertical scale and Finding Cost in $/boe on the horizontal).

Figure 1

What happened to Arco, Amoco, Mobil, Phillips, Texaco and Enterprise? Burlington, Kerr McGee, Unocal, Norsk Hydro? Gone!

What is my point?

It is that it is performance that ultimately decides the destiny of companies, not conspiracies - although I hear some Discussion Boards (e.g. the one on Premier Oil) believe something different!

And that over time, companies (have to) reveal enough about their actual, as opposed to promised, performance for investors to be able to see the truth. And for Executives to figure out their position relative to their competitors – and, if necessary, do something about it before it is too late.

Using Analytics

I have previously expressed my scepticism about how some of the “big data” learnings from other industries can be applied in oil & gas and I confess that I still need paracetamol for my headache when one of the behemoths of the world, or even of our industry, addresses the topic!

However, listening to some smaller companies with regard to the application of their software to subsurface applications, I have seen 4 or 5 different levels of insight:

1. Optimising a particular technology’s impact on production.

2. Figuring out which technology has the most impact on production.

3. Noting that in mature provinces recovery factors vary significantly between reservoir intervals, analysing what it is that most drives recovery factors.

4. Recognising what drives the production “sweet spots” in a basin.

5. And finally, concerning ‘prediction’ as opposed to ‘retrospection’. My thought is that we used geophysics, especially 3D seismic, to become predictive with respect to Deep Water reservoirs – but it took a long time (15 years, and lots of the Majors got there at roughly the same time). I think we can do a lot more with the combination of 3D seismic + logs + core + fluid analyses but at the moment this tends to produce ‘clouds of points’ - which cry out for the type of multi-variate analysis some can deliver.

Beyond this, I have encountered small companies that are using Analytics on for example:

Satellite data – many more satellites up there every day, with an increasing range and diversity of sensors: present all sorts of opportunities including onshore geology!

Simulation – the ability to simulate everything in a city (I heard about a virtual Singapore the other day) to undertaking ‘what ifs’ with North Sea infrastructure.

Multi-physics – how to integrate masses of satellite data, non-seismic geophysics, seismic, ‘rock hammering’.

Just my observations!

Understand your reservoir!

Some of you may have already browsed the OGA’s five year review of (UKCS) major oil and gas projects.

It is a sobering read, chronicling the various mishaps that beset 58 major projects executed between 2011 and 2016. On average:

·         fewer than 25% of projects were delivered on time (average of 10 months delay), and

·         projects were 35% over budget compared to estimates made in Field Development Plans.

In shape, these conclusions are similar to those of IPA in reviewing ~250 global FPSO projects.

QED: In the UKCS, and globally, major development performance is pretty miserable, with misses on 1^st Oil/Gas timing and/or budget and/or production delivery, sometimes all three.

The IPA study pointed to under-appraisal, that is, lack of understanding of the reservoir, its geometry and dynamic characteristics, as a key driver of poor project performance – in essence many folk designed the wrong production facilities.

The future of the UKCS relies in good part on the successful development of marginal discoveries – see OGA’s recent review. These leave no room at all for error and so getting your understanding of your reservoir spot on will be absolutely key.

In my humble opinion, our prediction, description and understanding of reservoir geometries, rock physical properties and dynamic performance remains weak – “could do better” would be written on our school reports. During the appraisal stage I think we can do a lot more with the combination of 3D seismic + logs + core + fluid analyses than we do and, as production develops, a lot more with 4D seismic/permanent reservoir monitoring and down-hole technologies.

Turning around the failing Exploration business!

Sorry to go on about it but Exploration performance has been poor for some years.

This is a rather superficial review of merely the latest poor year, 2016, focussed on the plummeting of discovered volumes to a historic low. But this narrow beam of light has allowed some to claim that this was simply the result of a dramatic fall in exploration spend…..

To really understand what has been going on, a more sophisticated, nuanced review is needed and for this I refer you to Richmond Energy Partner’s annual State of Exploration reports, the most recent of which was released in May 2016.

Where to start: commercial volumes fell to an all-time low, commercial discovery rates were as low as 1 in 12, Finding costs rose, much geology need $60/bbl to be economic etc etc. I look forward to their May 2017 report, I do not expect a dramatic improvement.

Let me be clear – in my view, Exploration has been, and is, failing as a Business!

Are there any root causes? Let me try a few….

1.      We became hooked on Deep Water but this has run its course; discovery volumes and success rates there have collapsed – we need to find new, different, frontiers.

2.      We have also become hooked on huge 3D surveys and forgotten or mislaid the fundamentals of petroleum exploration.

3.      Geoscience interpretation skills have weakened.

4.      There are too many ‘minnow’ companies, not underpinned by strong technical skills and knowledge. And with little financial muscle.

5.      Many company boards are not equipped to run Exploration as a Business.

How can this be turned around?

Firstly, we need to recognise that:

Petroleum Geoscience and Seismic Interpretation are not the same thing!

Excellent Petroleum Geoscience integrates stratigraphy, sedimentology, structural geology, geochemistry, petroleum systems analysis, non-seismic geophysics and of course seismic interpretation. Big companies – the Majors and the bigger E&Ps - should still be able to do this. If a company is determined to stay ‘lean’, then it will need to outsource – trickier than having most of what you need in-house but good people are out there!

And…..

Senior Management/Boards need to (be able to) execute a process of “Quality through Choice”, a proven methodology for improving exploration success rates, meeting targets, whilst staying within budget.

Secondly, 'pure play’ Explorers have two further problems:

As companies they have only 'worked' when oil prices were rising so much that equity holders were willing to pump more money in.

And…..

Where do they go - new Frontiers or existing provinces?

It would be easier to raise money for a spittoon manufacturer than to raise equity funding for a ‘pure’ exploration company. So this implies a viable company needs to include production to yield the cash flow for funding exploration.

Where do I have in mind?

Well, North Africa, the Caribbean, East Africa are certainly worthy of consideration. West Africa probably not.

Possibly the North Sea though we would have to figure out how to make currently marginal fields economic…..

Unconventionals are a possible theme: could a European regional company be built that is focussed on the Kimmeridge Clay and/or the Bazenhov and/or the Domanik?