Four Grand Challenges

Comments on Jodrell Bank Speech

Theresa May, British Prime Minister, May 21st 2018, Macclesfield

In yesterday’s post I had high expectations of scooping a major news story, but no. Maybe it’s because I don’t own a television, but I am very disappointed by the lack of coverage of a speech that history may look back as a turning point when we, “as a nation” – to borrow a phrase, shifted our focus from banking and finance back to inventiveness and engineering. Maybe that’s just my hope though.

I’ve listened to radio 4 and searched on the BBC and ITV websites, but all the references to the speech are in relation to Brexit and are all sound bites. They all miss the point entirely.

The speech was full of historical rhetoric about how great we used to be in science and name checked a roll-call of the great and the good. It therefore managed to tick both the jingoistic and nostalgic boxes. This was, however, not a light-weight speech but instead sets out a direction of travel and intent that we should all be aware of, because it has the potential to change our industrial history.

The full speech can be read here https://www.gov.uk/government/speeches/pm-speech-on-science-and-modern-industrial-strategy-21-may-2018

Like with Harold Wilson’s “white heat of revolution” speech where I didn’t comment on his pro-soviet views, I will also not comment on the Brexit views contained within this speech. That is as divisive and full of misinformation as was the capitalist/communist argument in the 1930s to 1960s and a rabbit hole that yesterday’s media went straight down – missing the point entirely.

Here are some of my highlights of the speech. Some of these, as predicted, do echo the structure used by Wilson in 1963, though to be fair, perhaps it was closer to the 1961 speech to congress by JFK [link].

On the scale of change of the 4th Industrial Revolution we now face, referencing of 1945 Britain

Their grand-parents lit their homes with oil lamps and travelled by horse and cart, but they would live to see jet travel and space flight.

Echoing the 1960’s speeches

[…] the world today stands at the threshold of a new technological age as exciting as any in our past. Great changes in how we live, how we work, how we trade will reshape our economy and transform our society in the years ahead. This technical revolution presents huge opportunities for countries with the means to seize them. And Britain is in pole position to do just that […]

[…] But success is not automatic. We are at the forefront of scientific invention because we embrace change and use regulation not to stifle but to stimulate an environment for creativity […]

[…] Scientific research is a noble pursuit and a public good – whether or not it leads directly to a commercial application. But when a discovery does have the potential to create or transform an industrial sector, time and again British entrepreneurs have been the first to capitalise on it[…]

[…] However, the nature of innovation and progress is that new technology inevitably replaces old. And in the twenty first century, some parts of the country that once thrived because of innovation and technology has seen the jobs and opportunities of the past fall away […]

[…] Our challenge as a nation, and my determination as Prime Minister, is not just to lead the world in the 4th Industrial Revolution – but to ensure that every part of our country powers that success. […] Nurturing the talent of tomorrow – through more outstanding schools, world-leading universities and the technical skills that will drive our economy.

On Investment in Science and Technology

£7Billion in new public funding for science, research and innovation […] goal of 2.4% GDP invested by 2027 […] Could translate into £80 billion investment over the next decade.

On Education in new technology

£26K tax-free bursaries for new teachers in priority subjects […] New T-Levels as good as A-Levels […] New Institutes of Technology […] National retraining scheme to help workers of all ages adapt their skills to the jobs of tomorrow.

On other elements of the strategy

Renewing and extending our infrastructure with faster trains, bigger stations, better roads […] Delivering the next generation of mobile and broadband connections […] Right regulation, modern employment standards, effective corporate governance.

At this point in the speech Theressa May laid out what she calls 4 grand challenges. Noting that it’s hard to predict exactly what breakthroughs lie ahead, she set out a Mission for each of the challenges with promises of more to come. So stay awake!

Grand Challenge 1: AI and data

Mission: Use AI and data to save lives.

In short use AI and data to predict diseases that kill people which if detected early are treatable.

Grand Challenge 2: Healthy Ageing

Mission: 5 extra years of healthy living by 2035.

Use technology to keep people happy, healthy and independent in their own homes, change employment responsibilities and innovate new products.

Grand Challenge 3: Future Mobility

Mission: Only zero emission vehicles by 2040

We pioneered trains and jet air travel, so this should be a doddle. A bit light on details though. But get on with it, we invented Formula 1 for heaven’s sake.

Grand Challenge 4: Clean Growth

Mission: Halve energy usage of new buildings by 2040.

Well pretty much what it says on the tin for that one.

These four missions are just the beginning – and in setting further missions across the four grand challenge areas, we will work closely with business and [the private] sector.  In each one of these four missions, scientific and technological innovations have the potential to create jobs, drive economic growth across the country and deliver tangible improvements for everyone in our country.

Conclusion

This is the first use of the term “4th Industrial Revolution” by a British Prime Minister. It shows a recognition that big changes are underway in the structure of society and the way it integrates with the world of work and therefore inevitably in the distribution of wealth and allocation of capital.

The OGTC in Aberdeen must be a happy place today, if there is anything to note for them there will be much more funding for institutions like them and their influence on policy can only increase.

Of the four “Grand Challenges” it seems to me that “AI and Data” will be required for the other three too, so the structure is a bit wrong. The missions however seem like a good concrete way to lay things out – though, to be fair, they are not really up their with JFK’s mission announcement at Rice University in 1962 [link]

At least she didn’t say : We didn’t choose to go to Cheshire because it is easy, we do this and the other things because they are hard. Have you seen the potholes on the M6 or the price of a train ticket to Prestbury?

Though technology may even have reached that far North. I am reliably informed you can now get an Uber in Prestbury. There is – exactly – one. British enterprise knows no bounds.

Industrial strategy revisited

Today, May 21st 2018, the UK Prime Minister, Theresa May is scheduled to give a speech regarding AI and the use of health data. This is the start of the revelation of the UK government’s new industrial strategy. From my vantage point, I see this political response to be part of the Fourth Industrial Revolution. My post was written (and published) before this speech and is a naughty attempt by me to see how well her speech writers know their political history. I have framed this in the terms of the Oil and Gas industry, Mrs. May’s speech will address Health Tech, but maybe some of the broader themes will resonate.

Industrial strategy is a something that the government hasn’t really majored on since the days of Anthony Wedgewood Benn.  They do say that history doesn’t repeat – but it does echo. This post draws on the “White Heat of Technology Revolution” speech given by Harold Wilson in October 1963.

To provide some context, Mr. Wilson’s speech was given during the early days of the 3rd industrial revolution. At this point we were seeing the start of computerisation and automation. Within a few short years we would see: the end of the typing pool; the death of the statistical time-and-motion studies; ledgers would be replaced with spreadsheets; and punch cards with magnetic tape with hard disk drives.

Unlike Mr. Wilson, who basically suggested that we better get on board with computerisation or we are all doomed; it appears that Mrs. May’s speech is going to suggest that AI can help cure cancer. Maybe it’s true that you can catch more wasps with honey than with vinegar. Mr Wilson’s political approach led, eventually, to the “Winter of Discontent” and the inevitable computerisation/automation led to the mass unemployment and the industrial upheaval of the 1970’s. Perhaps there are “interesting times” ahead?

I’ve taken some liberties by extracting parts of the 55 year old speech and reframed them. Perhaps you, too, will hear the echoes of history and see the implication of the change that we now face. For a transcript of the full speech have a look at this link

White Heat of Technology in Oil and Gas

(with apologies to Harold Wilson)

Now, this morning, I present this blog post to the world, the oil industry and the 4th Industrial Revolution, because the strength, the solvency and influence of the oil and gas industry which some still think depends upon nostalgic illusions or upon sub-sea posturing – these things are going to depend in the remainder of this century to a unique extent on the speed with which we come to terms with the world of change.

There is no more dangerous illusion than the comfortable doctrine that the world owes us a living […..] From now on The Oil Industry will have just as much influence on energy supply as we can deserve. We have no accumulated reserves on which to live.

It is, of course, a cliché that we are living in a time of such rapid scientific change that our children are accepting as part of their everyday life things which would have been dismissed as science fiction a few years ago. We are living perhaps in a more rapid revolution than some of us realise. The period from 2018 until the mid 2020’s will embrace a period of technical change particularly in production methods, greater than the whole industrial revolution and period of computerisation that went before.

It is only a few years since we first talked about digitalisation […..] Let us be frank about one thing. It is no good trying to comfort ourselves with the thought that digitalisation need not happen here; that it is going to create so many problems that we should perhaps put our heads in the sand and let it pass us by. Because there is no room for Luddites in our industry. If we try to abstract from the digitalisation age, the only result will be that the Oil Industry will become a stagnant backwater, pitied and condemned by the rest of commerce.

[….]

Because we have to recognize that digitalisation is not just one more process in the history of computerisation, if by computerisation we mean the application of technology to eliminate the need for data gathering and analysis by middle-management. The essence of modern digitalisation is that it replaces hitherto unique human functions of: risk assessment; judgement, decision making in the face of uncertainty; and ultimately action taking. Now digitalisation has reached the point where it commands facilities of memory and of judgement far beyond the capacity of any human being or group of human beings who have ever lived.

[….]

Or listen to the problem in another way. We can now set a machine learning system so that, without the intervention of any human agency, it can produce a new set of algorithms smarter than itself. And when these tools have acquired, as they have now, the faculty of unassisted reproduction, you have reached a point of no return where if man is not going to assert his control over machines, the machines are going to assert their control over man.

[….]

The problem is this. Since technological progress left to the mechanism of private property can lead only to high profits for a few, a high rate of employment for a few and to mass redundancies for the many.

[…]

Now I come to what we must do, and there are four things:

  1. We must produce more digitally trained engineers
  2. Once produced we must be more successful in keeping them in the industry
  3. We must make intelligent use of them
  4. We must organize the oil Industry so that it applies the results of their insights to the efficient production of hydrocarbons

[…..]

Relevant, also, to these problems are our plans for on-demand cyber training and MOOC’s (Massive Online Open Courses). These are designed to provide an opportunity to those who have not been trained in digital methods to do so with all that the internet and mobile technologies can offer.

[…..]

I have talked in other companies to ex oil-and-gas digital-workers who have left the industry. It is not so much a question salary; it is the poor valuation put on their work by our industries; the lack of interest in their work; and the inadequate provision of digital infrastructure and equipment. It is because in many cases in the Oil industry today, promotion of those versed in technological methods and their new ideas for ways-of-working are thwarted by middle management.

One message I hope this conference can send out, not only to those who are wondering whether to leave the industry or not, but to those who have already left is this: we want you to stay here. We want those of you who have left the industry to think about coming back, because the industry is going to need you.

[….]

The oil industry that is going to be forged in the white heat of this revolution will be no place for restrictive practices or for outdated methods on either side of IT or the Business. We shall need a totally new attitude to the problems of educating for changing working practices. If there is one thing where the traditional philosophy of capitalism breaks down it is in the training for digitalization, because quite frankly it does not pay any individual operator, unless it is very altruistic, quixotic or farsighted, to train the digital workers if it knows at the end they will be snapped up by some unscrupulous firm that makes no contribution to the training. That is what economists mean when they talk about the difference between marginal private cost and net social cost.

I’ll leave you to read the original and draw your own conclusions, I don’t agree with all the cut-and-thrust and pro-soviet views expressed but there are echoes from history that we ignore now at our peril.

Image Credit is from MI5. Oh, and if you like a good conspiracy theory have a look at the denials on MI5’s website about the alleged plot to bring down the Wilson government of 1974-76, and – interestingly – that George W Bush was head of the CIA (who knew? He kept that quiet). https://www.mi5.gov.uk/the-wilson-plot

 

 

Oil Companies Can’t Innovate?

I have just returned from two digital-operations conferences in Aberdeen. There was a common complaint among technology providers. They complained constantly that oil companies are slow to make decisions and don’t innovate (or specifically – buy their products). Some vendors even suggested that oil companies were 20 years behind the curve – that there are proven technologies available and in use in other industries that are yet to be deployed.

Of course, this is demonstrably wrong. Other than space and defence, I cannot name many other industries that can do something comparable to placing a drill bit 3KM into the earth in a water depth of 1KM with an accuracy of a few tens of meters. Engineers do this with real-time information from the drill-bit being beamed across the globe to operations centres thousands of miles away. That’s pretty amazing.

In truth – much engineering innovation comes from service companies rather than oil companies. Lots of technology and information processing is applied to exploration and drilling, a lot less in production-operations. The split in innovation from oil company to service company can be traced to decisions in the 1970’s and 80’s, the efficiencies and breakthroughs arose from companies such as Schlumberger, Gearheart and Atlas. However, the super majors such as Shell, BP and NOC’s (National Oil Companies)  like Aramco still undertake loads of research and have come up with solutions – such as polymers, de-ionised water for injection and their own seismic interpretation algorithms.

Still the point is valid – the 4th industrial revolution will mainly affect industrial operations. There is a distinction between operations within the business of oil-field services, and operations within the production of hydrocarbons. Both have the opportunity to become more efficient. Despite the opportunity, I’ve witnessed the complexity of buying and lack of progress in technology adoption within oil company operations, and it’s very frustrating.

I had a conversation with a senior exec at one of the new independents. I asked him why new ways of working were not being adopted.  His answer was very interesting. He told me that his team had just completed a new well on an old field. The well cost about £20m, took about 8 weeks from spud to completion, and was flowing at 3-5K BBl/day. It was simple, quick, contained, could be purchased as a work-package and was very much business as usual. No disruption to the organisation. That’s a return of more than 100% pa, a payback period of less than a year, and simple.

New technology implementation (the types of activity I was proposing) couldn’t promise that sort of percentage (or absolute) return, sounded complex and would – inevitably – require significant change to implement within the organisation. He had a point.

But that’s not an excuse. One day, and it may be soon, the sort of margins available on wells will disappear. There will be fields where the lifting cost exceeds the sale price for crude – but where there are still significant hydrocarbons left in the reservoir. In these situations, the impetus to reduce the cost of operations will be provided by the opportunities for profit. Somebody will be interested.

Look at what happened with shale in the USA. Fracking is not a new idea. The innovation of shale came from the combination of planning drainage patterns, drilling accurately, hooking up without interruption and – crucially – increasing the rate of development while dramatically reducing the per-well cost. Once this approach to development was established, it was game on.

When the big boys bought in – I was at BG we bought into Exco [link] – they didn’t come to the low-cost shale drillers and tell them to adopt the big-oil processes. The ponderous decision making and bureaucratic approvals required for $100m HTHP that takes 6 months to plan and drill, would have been impossible to handle the programme needed for a campaign of sub 100K 4-day wells required for shale.

It’s going to be the same again. With the late-life fields and new players, someone is going to figure a way to get the operating costs per barrel in a late-life field down below $10/Bbl and the big-boys are going take notice and learn.

The innovation required is going to come from low-cost technologies combined with an efficient operating model. Clay Christiansen in his book The Innovators Dilemma [Link  ]examined the disk drive industry and how the “big-oil” of storage were out competed by start-ups with sub-performance (but cheap) technology. Once a foot hold was established in the market – the performance of the new technology rapidly improved to the point where the big buyers switched. This left the previous big providers to decay into obscurity.

The North Sea oil industry was a pioneer in offshore development and much of the current techniques for long-reach directional drilling, FPSO and sub-sea originated there. With the business opportunity afforded to entrepreneurs by late-life field extensions, now is the time for innovation in how to operate cheaply. On-shore Middle East can produce oil sub $10 / Bbl the Offshore North Sea is $45. It’s time to innovate that gap away. (link):

(OK, I know the figures aren’t that simple due to capex and taxes but the principle stands!).

Image credit: https://jillwallace.com/vignettes/2017/11/8/pimple-on-the-ass-of-elephant

 

 

 

Ocado, where’s my Avocado?

Can Ocado’s warehouse teach oil and gas a trick or two?

Today the BBC carried a story regarding a visit to the semi-automated Ocado warehouse in Andover http://www.bbc.co.uk/news/technology-43968495 . It made me think about what their basis of competition was and how this might apply to oil and gas.

Ocado is a company that embraced digitalisation early on, without perhaps realising that they were a leading light in the 4th Industrial Revolution.  What Ocado do is not conceptually difficult to understand. They deliver groceries. The value they deliver to the customer is very like that available from Tesco, Sainsbury and other on-line retailers. So what’s the difference?

There are four elements required to make this business system work:

  1. Establishing a source of supply (things to sell)
  2. A way to get customers to place and pay for orders
  3. Methods for grouping the contents of the warehouse into packages
  4. Efficient delivery from warehouse to end customer

All four areas are ripe for digitalisation to make them more operationally efficient and increase the return on fixed assets.
At first the innovation that Ocado brought was to digitalise the shopping experience. As others have caught up, I think that Ocado has understood that their business model is going to have to compete on efficient order-fulfilment.  Customers don’t care about how that’s done (so long as it is) but other retailers might, and they might be prepared to pay for the service.

To be successful (in the traditional sense) means maximising retained profit in the face of competition. Each of Ocado’s four parts of their operation can be disaggregated and sell services to different customers. This is the classic “value engineering” popularised by Tom Peters and his peers in the 1990s.

Consider one scenario for a moment.  Maybe Ocado should consider if more value for the warehouse comes from the exclusive use by them (because they can charge a premium for their excellent picking), or perhaps they supply capacity to others and capture value by fulfilling orders more cheaply than their “competitors” can. Charging their competitors a fee above their cost.

When they brain-storm their options for this part of their value chain, some things they may consider include:

  • Would making their competitors more reliable hurt their revenue coming from the Ocado website?
  • Would increasing the volume of orders handled increase error rates?
  • If their service suffered and took-down Tesco deliveries, whose reputation would suffer?
  • Would more volume lead to economies of scale and reduced costs, and more profit?
  • Is the way that they develop and use technology in their warehouse patentable? Is it a trade secret, can they license the method to others and help them set up their warehouses?
  • What if someone else offered this service, would they use it or choose to compete?

When the four elements are combined, competition comes from the likes of Sainsbury Online and the Tesco Website and Substitution from a traditional Supermarket. Each of the four main parts of the operation faces different competitors such as: Walmart for efficient sourcing; Ebay for customer experience; Amazon for warehouse management; and FedEx for customer package routing and delivery.

What I find interesting is that the basis for innovation and efficiency is all driven by different aspects of Digitalisation and I4.0, but the opportunity for innovation comes from the vertical integration of the four elements together. One day, the new model will have consolidated around new “digital design patterns” and the window will open for value creation through consolidation, outsourcing and specialisation within the value-chain.

This is a lead-in to my next post which I’m writing where I will consider if the move in the 1990’s to outsource everything “non-core” in oil and gas operators has left the previous generation of leading companies unable to digitally innovate across their value chain. This is because they no longer have the end-to-end knowledge to combine with emerging digital ways of working. If I am right, then future innovation may be driven by new players who have not outsourced their operations to a myriad of subcontractors. Interesting times.

Image credit: https://vivitherapy.com/product/avocado-oil-organic-virgin-1-litre/

 

 

 

 

 

 

Interview with Patrick von Pattay

I was introduced to Patrick [Link] by our mutual friend Short Allerton [Link]. We both worked with Short in Schlumberger days, but our paths had not crossed until recently. Patrick is an exciting individual who has worked on very interesting projects pushing the boundaries of future oil and gas practice in Upstream. We got on well and he shares many of my views on digitalization, and – importantly – our opinions differ about how things may develop in some areas. It was a genuine pleasure to speak with him and he has agreed that I may publish this interview on the blog.

GD: Good Morning Patrick, thank you for agreeing to talk to me about Industry 4.0. It sounds like you are very interested in the topic.

PVP: As you might have recognized I am very passionate about the idea of a disruptive change in the oil and gas industry.  Currently I am looking into the strategic implications of digital revolution that is surrounding us and what is likely to be a time of disruption and step-changes in productivity.

GD: I agree with you Patrick digital technologies will make a big difference in upstream oil and gas, I expect to see this most pronounced in operations of existing and new plant. In my view, some fundamentals won’t experience much change – such as how resource licenses are issued by countries and used as security in the capital markets.

PVP: Just because we have not yet identified the potential disruption does not mean to me that there cannot be any.  It just means  that we haven’t thought hard enough. If it were an obvious change then it wouldn’t be so disruptive as we’d all have the ability to respond. A disruptive completive threat, by its very nature, is likely to come from left field.

GD: I’m not convinced, but interested to hear what you think the changes will be in operations?

PVP:  Leaving aside access to resources, I think there will be three main effects of the digital revolution in upstream:

Increase in efficiency:

Automatisation will be key here and I expect that activities will include predictive maintenance, artificial intelligence based auto modeling, augmented reality supported operations, automated manufacturing, Internet of things, etc.

Increasing effectiveness.

This will result mostly from faster and smarter decisions. Advanced, more complex, more integrated and holistic modeling will enable us to make more educated choices.

Improved uncertainty / risk management.

The advanced and integrated modeling will enable us to model (and therefore manage) uncertainties all the way from the reservoir to the marketing of finished products and the trading of field percentages.

GD: Yes, I agree with you on those three for sure, though it’s a bit mother-hood-and-apple pie. That’s what we’ve always tried to do, and gradually we’ve been improving there over the years. What’s going to change?

PVP: Well of course we’ve been doing that! But, things are about to accelerate and we’ll see enablers for step changes – super and cloud computing is key to holistic asset modelling – but, beyond that especially in the way we contract and co-ordinate the supply chain I expect great changes.

GD: What trends are you seeing there?

PVP: Services of all kind are becoming a commodity. Initially, this is focusing only on basic oilfield services such as cementing.  I expect that this will lead to more choice for me as an operator.

Maybe I will not buy such services through classic service contract models any more, but through a web-based and horizontally integrated retail platform. This will increase my flexibility, control and drive down costs. Perhaps drill bits will become a line-item on Alibaba? And maybe this is the domain where we will see most disruptions in the coming years.

GD: I see how that can work. There have been automated purchasing databases before, mainly for supplier pre-qualification and compliance checking. Services like the Achilles system, but they’ve been directed towards procurement departments and not putting the power of supply-chain optimization directly with the end-user of products and services.

PVP: Yes, as time progresses and digitalization evolves, commoditisation will include more and more complex services. Already the service companies and EPCIC contractors are integrating their services and offering me solutions.

Combining this trend with digital technologies could make even the development of a complete oil field a commodity one day (as much as building an airport would be a commodity by then).

GD: How do you see this changing the industry for project owner operators?

PVP: We must expect new players to enter the market. To thrive in this situation means we need to find new differentiators, perhaps even re-invent our business model. This will mean perhaps developing even more complex projects and integrating services/solutions along the horizontal and vertical value chain.

GD: That’s very interesting. What I think you are saying is that the low-end easy returns from deploying capital to safe projects will be competed down to the cost of capital, so you you’ll need to do more difficult things where there is less competition. Can you expand on that a little, how can you use digitalization to achieve that?

PVP: Well of course, there’s the nub of the issue. I can’t tell you everything I’m working on of course, but let me give you three areas where I think we are likely to see disruption: The Value of Data, the use of Cloud Computing and What I call “Buying a Result”.

The value of data

Artificial intelligence is a key technology in digitalization. It will allow us to assist humans in many places and to achieve results significantly quicker / with higher accuracy. In any case the key will be to train the artificial intelligence based on distinct high-quality data sets. Considering such data sets as training material makes them an asset. Trading such data against trained models will be a part of the new business world. Like Google is the best search engine because of its accumulated experience, so it will be with oil fields. Once this is cracked, experience may result in enduring competitive advantages which can be monetized by turning data into decisions in minimum time.

Cloud computing

The cloud will be the only place to store and process data in the future.  It is the most secure and cost-effective way.  A whole new landscape of solution providers will arise from this.  The classic service and software providers are establishing their cloud solutions today.

The operators I talk to are concerned about locking up with one of them and being chained to their choice forever. Their data may become trapped. This is going to drive standardisation and open platforms.  These will allow plug and play of any software in the cloud.  The availability of such a platform and the guarantee of the provider to support the integration of any service / software will provide small solution providers with a new platform to offer their products and reduce the market entry hurdle for them greatly.  We can imagine this a bit like the different APP stores.

Buying a result

Today we still buy compressors and then maintain them. In aviation, some airlines buy only accident-free-human-miles-transported from an airplane manufacturer. They focus on planning routes, marketing seats and ensuring client loyalty.  Similar things may happen in our industry. Augmented reality allowing to scale the know-how of a single expert, Internet of things, big data analytics, predictive maintenance, etc. will allow various solution providers to offer services to us like the way airplane manufactures do today.  The E&P companies will transform into managing and providing more complex solutions and business models. This will include more and more gain share models.

GD: You do paint an interesting view. In your scenario data and machines look like they will take over. That’s bad news for any young engineers surely. Why on earth would you need any people? Are operators going to be run by hedge funds and lawyers?

PVP: Some people think that many oil companies already are! But, seriously, I believe customer focus, personal interaction, social competencies, and creativity will become more valuable. As more and more complex tasks are fulfilled by machines the role of the human will shift towards creativity and social interaction.  I am convinced we will be very busy thinking about things that we do not even imagine today as we are busy with the groundwork.  It will be great fun!

Look, we know that even after all the money spent on, and focus applied, creating an Amazon a web page, it is still not the key to providing the best possible service. It’s efficient for somethings, but sterile and not very interesting for others. Even Amazon is opening physical stores and Apple has the most valuable retail operation in the world. Human contact and empathy is still important.

The key will be to hook up with the client immediately and to ensure that he/she can’t live without your service ever again. The client has choices, so this must be done through excellence not through lock-in. In the domain of super-mega projects this might simply boil down to the ease of doing business with you.

GD: Thank you for your thoughts on this, it’s very insightful. Where do you think, we go from here?

PVP: Reflecting on our conversation, I might even agree that the oil & gas industry will not change in the fundamentals of exploration – development – production – abandonment.  But the landscape of players will shift due to digitalisation and this might be the disruptive change for us all.

GD: Thank you, and good luck. Will you please come back and tell me and my readers how you get on?

PVP: Sure, I’ll keep in touch, and I’d I love to have feedback on my thoughts

O&G –Development, Projects and Industry 4.0

In an earlier post [link] I introduced four areas of the Oil and Gas value chain that would change because of Industry 4.0 (I4.0). In this post I am going to present some ideas about what might change the activities occurring between finding a deposit of oil and gas and going into production.

There are four widely recognised phases during this period I’ll label these: Concept, Design, Construction and Commissioning.

There are many interacting functions contributing to this process besides engineering. These include: Project Controls, Stakeholder Management, Finance, Legal, Risk, Marketing, Contracting & Procurement. Because oil projects tend to range from 100’s of millions to 10’s of billions of dollars these activities can have more impact on a project’s viability than the engineering.

In this post I am not going to consider the changes that I4.0 will bring to the underlying technology deployed in a field (such as intelligent completions, sub-sea completion systems etc.) but rather will concentrate on the operator process of bringing a field from discovery to on-line production and how this may change.

CONCEPT SELECTION

Concept selection involves generating options for ways to develop a field – such as what type of platform, how many wells, where to sell the product, how to transport it etc. This involves assessing various trade-off’s between cost, production profile, technical risk and time to market.

This area is one where experience and networks count. Advisors add value here. Unless an operator is a super major, the number of concept selections processes undertaken during their development teams’ career can be low.

Concepts rely on relationships and contracts with external parties such as governments, partners and financiers. The goal of selection is to examine possibilities and choose the most promising to work up in more detail. Detailed work-up of ideas costs a lot and takes time, so it’s best to avoid re-doing it. Selecting the best concept is important.

Selection is through an assessment of feasibility and creation of valuable approaches for external parties aligned to their appetite to participate. Better modelling of risk/reward profiles and the ability of AI and machine learning to help with option generation and assessment will create change here.

To generate viable options and to make introductions to partners requires wide experience, a diverse set of skills and set of external relationships. Companies like io oil and gas consulting, Granherne, Genesis and Xodus and others are go-to companies for serious operators.

I4.0 will likely impact the work of these companies in three ways:

  1. Technologies will be adopted that enable better collaboration between parties and facilitate the exchange of information. This, by itself, will result in faster turnaround, reduced waste and lower cost.
  2. The value of networks and relationships cultivated by consultants to both source work and to introduce in related parties may reduce. Part of the value captured is because of “knowledge gaps” where players do not know all the parties who may be interested or how to contact them. It is likely that some of this role will be augmented with the introduction of automated agents. Reputation and relationships will still matter and will become a differentiator but it is likely that the ability to command premium pricing will be reduced.
  3. The value of experience will almost be wiped out. As an anology, consider how an app on a smart phone has given Uber drivers the ability to use the backroads of London like a black cab driver with 30 years personal experience. In concept generation, a system that constantly learns all the options that have been considered before around the world, combines them and add twists will provide novel approaches. This will mean the creative aspects of concept design will become increasingly automated. There is the potential for a google-like winner-takes all first mover advantage. Captured experience will lead to more opportunities for work and hence generate more experience. Perhaps we will see one consultancy decide that the value of knowledge will be higher than the cost of acquiring it and will start to work under cost price for the chance to become the first mover?

For concept selection, the differentiation will not only come from the depth of the accumulated knowledge-base but also from the ability to deploy emotional intelligence and maintain the confidence of stakeholders. Like many I4.0 opportunities value will be generated from blending human soft-skills with an ability to harness the power of the new machines and ways of working.

DESIGN

There are various iterations of design and “stage-gates” on the way from Front-End Engineering Design (FEED) to Detailed Design. For the sake of this piece I’m going to be broad brush in my approach, so apologies in advance to my engineering friends for the lack of detail.

There are four main areas within the Design phase that need to be addressed

  1. The engineering of components and systems
  2. The co-ordination of the design activity
  3. Developing the commerciality of design
  4. Maintaining the consistency to the original concept

Engineering of Components and systems

The engineering process has already been revolutionised by computational power and the transportability of information. No longer are drawings done on dye-line blue prints and red-lined in pen. The computation revolution included things like reservoir simulations, process simulation, CAD drawings and automated parts lists.

I4.0 will enhance the process by enabling more simulation – such as simulation of construction, operations and maintenance. The type of output that will be required is likely to change. As operations move towards more “digital twin” enabled processes the as-designed, as-built and as-operated models will require more detail and will contain more information. Therefore, I4.0 approaches will need to enable this by, for instance during design, automatically populating tags for equipment, and providing normal operating ranges for instrumentation alarms – all pulled directly from manufacturers information.

AI systems in the future may even make suggestions for more efficient ways to plan pipe-runs, or help by making suggestions concerning process engineering or instrumentation. For an example of this type of guidance look at MS Word. As I type I get underlining in blue when I misspell a word and in red when my grammar is off. This is accompanied with helpful suggestions should I want them. Engineering design systems in the future may do similar tasks alongside engineers.

We will see an ever-expanding repository of re-usable design components which will continue the progression towards modularisation and re-use of designs. Standardised design and construction (where appropriate) will reduce costs. Couple this with additive manufacture for specialist parts and design work may move away from run-of-the mill towards assembly of modules and the design of very specialised be-spoke components.

Co-ordination of design activity

Anyone who has worked in a large-scale engineering design office will say that much of the work (and most of the errors, and most of the wasted cost) is incurred in the co-ordination of work between engineering teams, subcontractors and clients.

Firstly, there is the problem of controlling the internal integrity of the design. For instance engineers need to know things like flow-rates, reservoir pressures numbers of wells etc. I have seen examples where the reservoir group and the engineering team will progress for quite some time when their assumptions have diverged. Same goes for all upstream-downstream processing, topside weights, fire-systems and instrumentation. This is an information co-ordination problem. I4.0 will help because there will be fewer engineers required to work on design due to automation (therefore less co-ordination will be required) and where it is by “compiling” the individual designs into an evolving a digital-twin, techniques from software engineering used to co-ordinate source code, apply updates. automate error checking and run-test can be used.

Sign-off between clients and contractors means document trails can be an immense source of frustration. The control of versions and reviews often needs a whole department of people dedicated to it. Contracts are tied to sign-offs and all have time-limits that must be observed. I4.0 has the potential to apply block-chain audit trails, digital twins, version control & roll-back. Block chains can even be used to automatically transfer value between parties to settle contracts.

Managing Interfaces is a whole discipline. Different teams – sometimes different companies – design parts of the plant and it’s important that pipes and wires all match up when the modules are constructed and delivered. Again, design component submission into a digital twin from the start can detect problems and eliminate this type of error from propagating.

There is schedule and cost management activity required. Normally this is either a P6 or MS-Project based process with email reporting of progress required from all parties and manual co-ordination to provide an approximation of current progress. This tries to highlight any dependency busts that have blocked the project and provide forecasts to management. Designing within a digital twin, where the design process can be simulated, will enable a risk-based approach to schedule and cost management to occur automatically providing visibility and risk-control.

Developing the commerciality of the design

I4.0 will require changes to decision process here so it may take a while for things to change. Good design provides both construction-dividends and operation-dividends. Designing a plant in a way that eases construction currently increases the cost of the design work. I4.0 automation may reduce or eliminate this extra cost, but the types of material or module may be more expensive to buy but cheaper to construct – balancing those trade-offs are difficult both because the information and the consequence of decisions are not visible to everyone, and procurement rules may favour a least-cost approach. I4.0 may help to present more transparent business cases and enable more informed decisions to be made.

Operation-Dividend is a hard one to address. Even today there are information, models and design files that can be created and could be of great value to operations. They may never be created or delivered to clients because of cost pressure. Many Oil and Gas project procurement processes are based on lowest cost supply – this drives out added extras which are not strictly necessary during design, but would have produced dividends later in the life-cyle of the project.

It is my belief that as I4.0 techniques become established and drive efficiency in the design process there will be a natural tendency for these dividends to arrive, however by forcing the issue now – operators could accelerate the adoption of I4.0 techniques among their suppliers. This they should do.

Maintaining Integrity of the Concept

It is a phenomenon that design decisions are taken for good reasons in the depths of the project and these can, unintentionally, add up to a fundamental change in the economics of the concept. These decisions are taken for good reason, but without the impact being fully understood.

A forward-thinking operator may employ representatives from the concept team to assure that, during design, no decisions are taken that alter the concept economics without due care and attention. Even then, however, it may be very difficult to detect all the small changes that may add up to a problem later on.

I4.0 means not only will this process be built into the “compiler” checks for the design but also it will have knowledge of the assumptions underlying the concept. The project owner will be able to track real-time fit between as-designed facility and the expected concept value. This means also that the validity of the concept economics can be monitored as external events challenge the assumptions made. By setting appropriate risk-tolerances actions can be taken to steer the design of a project faster the normal stage-gate system.

CONSTRUCTION

This is a huge topic with lots of interaction between subcontractors, yards, welders, steel producers, component suppliers, machinery vendors, site logistics etc. etc.

The order in which construction happens can be crucial. it’s an involved problem to solve because sometimes something can’t be built until a large piece of equipment has been manoeuvred into place. Sometimes there are contingencies such as road access or camp construction or constraints on access to lifting equipment time. These types of scheduling problems, full of constraints, dependencies, lead-times and uncertainties interact with physical layout. This type of problem is one that AI based simulation and machine learning has demonstrated value. I expect that the planning of construction work packages and sequencing will become much more efficient with I4.0.

I4.0 is likely to deliver technology in terms of sensors, autonomous survey vehicles and 3D model population that provide accurate tracking of progress against schedule. There are likely to be wireless condition sensors provided with equipment (such as rotating machinery) to ensure that it is properly maintained in the time before delivery and installation. This will save pre-installation maintenance and avoid delays.

We are likely to see technologies such as automated reporting of equipment positon on the way to site meaning that schedules and daily work-plans can be optimised to the prevailing circumstances.  Block chain style transactions are likely to reduce the formidable overhead associated with contractors and their execution of work. The same technology that can provide better than ISO-9001 trail of supply, fitting etc.

I expect to see more automated construction, on-site manufacture of parts (3D printing) and more just-in-time manufacture and delivery of equipment. All of this is going to combine with better visibility of progress to lead to faster construction, with less waste (and hence less cost) and deliver much higher quality and predictability.

COMMISSIONING

Commissioning of new plant as it starts up and before it is presented to operations is likely to change too. Simulation and machine learning will mean understand that different parts of the plant need to be brought on-line and in sequence. Experience and learning will shine a light on areas most likely to fail and their failure modes. Some potential failures will be detected and ironed out prior to attempted start-up.

As plant is brought on-line equipment settings will be noted in their “tags” and can be automatically compared to the as-designed expectation and the manufacturer’s recommendations. Equipment performance can be tracked through sensors from day-one, this will help with predicting failures in the future. Intelligent software can be used to highlight unexpected situations.

The automated learning and recording of the start-up procedure and equipment settings can be used by operations for plant re-start and for comparing as-operated settings to as-commissioned to track where, when and why parts of the plant are being changed.

CONCLUSION

Industry 4.0 has the potential to provide substantial benefits to the development of oil fields. Many of the processes described above have been technology back-waters relying on manual systems, ad-hoc applications and a lot of tacit know-how. I believe that this will change. It will take new technology and also take new ways of working. The supply chain will need to respond. FEED, EPC and PMC contractors who get on the bandwagon first will create the opportunity to assemble unassailable leads and take a dominant market-share in the way that Google did for internet search.

(Image credit : https://www.gie.com/)

 

 

 

 

 

 

 

 

 

Levels of Automation in Oil and Gas

One of the aspects of the 4th Industrial Revolution [LINK] is automation.

I am often asked if automation could ever add value to oil and gas? I contend that there is a good reason to think it will because benefits could come from:

  • accurate control and adjustment leading to higher throughput;
  • self-repairing (or self-scheduled repair) leading to higher uptime;
  • more accurate execution of plans by reducing manual error; and
  • less distracted management leading to higher-value decisions;

Many people are sceptical that we can ever “automate” an upstream oil and gas production facility.  I agree that “full” automation is unlikely, but I would argue that partial automation is already present. What we need then is a way to describe “levels of automation” so we can define what we are talking about and reach agreement about what to do.

Autonomous cars are in the news for good reason right now, and are making great progress. Perhaps we can create a common language for “level of automation”. The SAE introduces itself as:

SAE International is a global association of more than 128,000 engineers and related technical experts in the aerospace, automotive and commercial-vehicle industries

It has defined 5 levels of automation that has now been adopted by the US Department of Transport. Here’s an explanation from wired magazine [LINK].

What dimensions could be used to classify degrees of oil and gas production automation? My definition of the process of automating is: “Reducing the friction between sensing what is going on and taking the right action”. This can be used to underpin a maturity matrix.

If we can sense what’s happening, reduce the friction before acting to zero and be exactly right in the actions we take – then this achieves perfect automation. Of course this then leads to the need to define in more detail: sense, friction and right.

Some of the steps that can lead to more automation are:

  • Improved sensing of the environment;
  • Distribution of sensing data;
  • Transformation of data into information (e.g. production vs. target);
  • Exploring related information, history and context (e.g. maintenance records)
  • Understanding the consequences of the information presented (prediction);
  • Checking possible actions and their impact (simulation);
  • Delegating decisions to reduce management delay; and
  • Feeding back observed results to scientifically tune future predictions (learn)

Contact me for more information about how it is possible to incorporate the above into an assessment of your organisation’s automation maturity and readiness for change.