Category: Industry 4.0

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/

 

 

 

 

 

 

Industry 4.0 – Are we there yet?

Something’s up. I was reviewing my web-stats for this site and I found that since Jan 2018 one post has been read 1000’s of more times than any other one. This one: Innovation and Productivity with the Fourth Industrial Revolution.

About 3 years ago,  I started to talk about how relevant to the Oil and gas industry were things I had been studying about the 4th Industrial Revolution. At that time no one had a clue what I was talking about. Some thought I may have gone mad. I’m glad to say that things have (mostly) changed.

Who’s talking about it?

Since 2018 I’ve seen the term being used by a number of my peers in Oil and Gas, and when you search on this and combine with the term “Digitalisation” It becomes obvious that there is a major movement underway.

Steve Ashley uses the term in his article: Digital, data and taking control of our own destiny and its also used in this press release from Petrotechnics.

Today this announcement from CapGemini helping Statoil with a 3 year project to create a digital roadmap.

How to assess a digital project

There are still a few fundamental questions that every digitalisation project should be able to answer. Below is your starter for ten, and – yes – you may confer:

Examine the project value:

  • What is the primary business driver;
  • Does this project fulfil the agenda of the CIO or the COO;
  • What is the net cost of this project;
  • When will I see value (hint: the choice is either this year, or 3-5+ years out); and
  • Is this a platform investment or can it ride a set of network effects?

Examine the project risks:

  • What things will prevent me from realising the planned benefits;
  • How much change will be required in the way we work;
  • If I do this, does it prevent me from doing other things;
  • How likely is it to require more money than I’ve budgeted for; and
  • What happens if I wait and do it later?

These criteria (and others) should be considered for every project.

Enterprise level

At the enterprise level there are a couple more  things that need to be considered including:

  • How does this project fit into my portfolio of digitiallisation initiatives;
  • As my business gets more digitalised, how am I addressing digital integrity; and
  • Should my HSSE function be renamed HSSED?

Further reading

I wrote an article for ITProportal for some of this and here is a note on project portfolio prioritisation that I wrote a few years back – Introduction to Prioritisation V 1.0.

Five Digital Vectors

Frameworks for Digitalisation – Part 1

I’ve been working on frameworks that help me describe concepts around Digitalisation in upstream oil and gas. I plan to publish these in several formats but so far I’ve been too busy to do this to my satisfaction – so I’m going to put them out here for comment and then work them up as packaged tools.

This first framework – five digital vectors – is designed to set the context for the strategic intent of a digitalisation initiative. This is important because senior management had better know why they are embarking on programme of change, what they expect to get from it and where threats to it will come from.

I was recently talking to the CEO of a multinational engineering consultancy based in Norway. To slightly protect his identity, I’ll call him Egil.

Egil:  “Gareth, you know [insert Big 4 consultancy here] was just in my office telling me that digitalisation was going to radically alter my business. They said just look what NetFlix did for the video store. It must be important or they wouldn’t be here. But I’m busy and, frankly, I don’t get it”.

Communicating strategic intent is important. I am as guilty as anybody about trotting out tired lines about how digitalisation will disrupt industries and then helpfully pointing out that Uber has no cars, AirBNB no property and Amazon no shops. This may be intriguing but it’s no longer precisely true (as all three are busy making strategic bets in traditional assets), and it’s of very little help if you’re in Oil and Gas wondering how this applies to your business.

Using this Five Digital Vectors framework provides a way to classify the objectives of an initiative, how innovation in the area may cause competitive shifts and explain where to look in order to measure success. There are Five main vectors for digitalisation. They are:

  1. Pure Digital
  2. Digitally Enhanced Products and Services
  3. Digitally Efficient Operations
  4. Digitally Effective Supply Chain
  5. Digital License to Operate

I’ll explain a little about each of these, and then hopefully you’ll get the idea. If you take each in turn you can look for potential disrupters and initiatives and decouple them. Some of these will be more likely to impact your business than others. At least now you can decide which few to concentrate on first.

Vector 1: Pure Digital

Pure Digital strategies work when a product can be codified as information. Think Music, E-books, Films. Once the physical product is removed massive scale economies accrue to storage and distribution. What is called “long-tail” economics kicks in around inventory and specialisation, customisation and choice. In Oil and Gas, we may see some spare parts digitised, emailed and then 3D printed on-site. This will reduce carrying costs and delays. We may also see pure information products trade more freely (such as production forecasting, planning, sub-surface models, training data sets and educated machine-learning algorithms).

Vector 2: Digitally Enhanced Products and Services

Digitally enhanced strategies arise when the fundamental “product” becomes augmented with information. For instance, Uber generates a fair portion of its demand not only on price, but also because it provides information about where the cars are, when they will arrive, the route they take and the price you will pay. They then ease the transaction by collecting payment and supplying receipts. However, all the digitalisation in the world will be useless without the underlying physical product (in this case, a car to take you home). In upstream oil and gas we may see that a supplier of products such as spare parts, services or even crude oil become a preferred option when they supply accompanying information before their wares arrive and when they keep you informed while they are in service.

Vector 3: Digitally Efficient Operations

In oil and gas this is the area where I am witnessing most digitalisation activity.

Using information within your own business to reduce waste and increase accuracy is hardly a new idea, but digitalisation changes the game. As more information becomes available – because of better connections, more sensors and accumulated history – so it becomes possible to change the way you do things. Prioritisation, scheduling, just-in-time: these concepts work better when you can access more information and use it sensibly. Today’s engineers entering the workplace can probably not remember a world that didn’t have an iPhone and Google (Google is almost 20 years old). So, they are used to being able to think of a question and get an answer quickly. If you can harness this creative real-time problem-solving ability (by making information available) you can improve your operations.

Vector 4: Digitally Effective Supply Chain

Both vertically and horizontally there is potential to add value through more efficient exchange. The digitally efficient operation strategy will reduce the waste and hence cost within a single company (see Porter on what it will do for price). Supply chain strategies focus on removing friction between companies so inter-company waste will also reduce. This is, in many ways, a move from Digitally Efficient Operations to Digitally Efficient Industry. It is about expanding the focus from the individual company to the collection of companies.

For this to work requires standards, data compatibility and platforms where buyers and sellers can transact. Some suppliers (think about a stationery company) will supply various industries – say automotive and oil and gas. So eventually some standards will need to be cross industry, whereas others (say for drilling services) won’t be.  Though the benefits can be large, there are two main problems: co-ordination of participants; and allocation of cost and benefit.

Vector 5: Digital License to Operate

This is an interesting insight that came to me when I was discussing the apocryphal case of a town inviting bids from contractors to build a pipeline through it. One bidder offered to expose in real time the contents of the pipe, the corrosion status, inspection procedures and compliance, the leaks and seeps and other such. The other company claimed it was confidential. Guess who got the permission to build.

Whether the information was confidential or whether the quality of it and how to access it was suspect, I don’t know. But we see similar exposure of operational data for services such as trains and busses through simple APIs. This data is then “mashed up” by active citizens for public good to help people plan journeys or avoid breakdowns.

In the future, perhaps it will be a requirement of regulators that operational, safety and environmental data is made available to the public in real-time, if not – then you won’t be allowed to operate your field. Once that data’s out there you can expect to be held to account for your actions. Welcome to CSR in Industry 4.0.

Summary

The five vectors described here help to provide a primary direction for an initiative. For maximum impact, like all good vector mathematics, the magnitude of value delivered will increase as the direction of the vectors align. This tool helps to focus the mind on the primary vector and provides insights to the effect on the others to enable informed choices to be made.

As always, email me direct or leave comments here and I’ll do my best to respond.

Image credit http://www.kimonmatara.com/vector_ops/

 

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

Digital disruption landscape for upstream oil and gas

I was recently asked by a client for assistance in examining how their business strategy might be affected by Digitalisation. This company is a mid-tier upstream operator with a mix of assets mostly non-operated but does have some where it is the duty-holder.

So I’ve propose the following five point map to classify where the disruption could occur in the upstream business. This helps to define not how, or when,  but where disruption is possible. This framework helped us examine what threats and opportunities are likely to emerge in each area and I thought I’d share.

Please feel free to comment and I will keep this updated  for the network.

Demand for Oil and Gas

  1. Digitalisation in the wider economy may affect the demand for energy through different transport usage, renewable control, demand management and micro-grids.

Access to Resources

  1. Access to operate resources may change as national owners find different partners to help them monetize geological wealth
  2. Opportunities to become a non-op partner may change as operators get more certain about their outcomes and require less diversification in their portfolios
  3. Competition for resources increases as development and production services become purchasable/tradeable activities
  4. Transparency of operation and methods to extract changes what is required to retain a license to operate
  5. Better techniques for collecting and interpreting data leads to more resources being found and better development pre-planning (westwood puts the commercial success rate at between 30% and 50% https://www.fircroft.com/blogs/less-drilling-more-success-the-state-of-exploration-drilling-so-far-in-71921114313 )

Development and Operation of Resources

  1. Digital planning and modelling combined with better logistics and manufacturing/construction techniques reduces the capital requirements for fields meaning lower barriers to entry
  2. High frequency low-cost drilling reduces the sunk-cost nature of investment, reduces cyclical volatility of supply/demand imbalances and hence expected return on capital
  3. Better information leads to increased recovery factors and ultimate value of assets. (Currently this is estimated to be below 40% http://www.spe.org/industry/increasing-hydrocarbon-recovery-factors.php )
  4. Better information, co-ordination and reduced waste leads to lower operating costs per hour of activity (for some bench marks check here https://knoema.com/rqaebad/cost-of-producing-a-barrel-of-crude-oil-by-country )
  5. Better prediction of failure and real-time optimization of fields leads to higher efficiency and hence accelerated cash-flow (currently 73% in North Sea https://www.ogauthority.co.uk/news-publications/news/2017/uk-oil-and-gas-production-efficiency-rises-to-73/)

Sale and transport of product

  1. Better information about the crude quality and refinery / other consumer plant configuration leads to higher yield / lower cost processing
  2. Information about the location of supply and demand enables better optimized transportation and reduced costs
  3. Better prediction of both future production and future demand enables balancing of both. This leads to changes in the premium available from trading and who captures it

Human elements

  1. Automation leads to different models for distribution of wealth among the middle classes (no longer based on work)
  2. Automation leads to people choosing to add creativity and seek challenges in different environments and under different conditions
  3. Changes to the working motivation scheme means modernization is required for operating model for Oil and Gas industry to attract talent

 

 

Image credit: https://www.pmfias.com/natural-gas-distribution-world-india-petroleum-gas-value-chain-upstream-midstream-downstream-sector

 

 

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/)

 

 

 

 

 

 

 

 

 

O&G – Exploration and industry 4.0

In an earlier post [LINK] I briefly introduced the four areas of upstream value chain that could benefit from the 4th Industrial Revolution. Here I put forward some potentially controversial points about how this may (or may not) affect Exploration.

First of all my definition: Exploration is concerned with finding and appraising new deposits of Hydrocarbons trapped under the surface of the earth. It’s the identification of these that I am addressing here, not how (or if they can be) exploited.

There have been many advances made in technology in the previous 25 years that have transformed the process of finding deposits. The two most notable have been around the use of remote sensing through Seismic Data, and the accuracy with which deviated wells can be drilled. Seismic acts like an x-ray into the composition of the rocks, while new wells use precision direction control and combine it with analysis of real-time feedback from rock measurements surrounding the drill bit to let operators steer the trajectory in real-time.

Many of the advances that have been harnessed could legitimately be described as pioneering in the technology of sensing, big-data, simulation and automation. These are the key technologies underpinning the 4th industrial revolution. Exploration got there first.

In my work with small companies seeking investment I continue to see a slew of new start-ups with fancy seismic algorithms claiming to be able to spot even more obscure sources of previously unidentified hydrocarbons. Maybe they work. Who cares?

In my view the major gains from the 4th Industrial Revolution have already been captured in exploration. Perhaps we are close to entering an era of more stable oil prices – driven by: elasticity of supply from shale; abundant reserves released from both tight reservoirs and hydrates; and managed demand through smart technology, electric drive-trains, renewable generation and batteries. So the commercial pressure to find obscure resource pools may have gone.

In the North sea there are over 300 pools of hydrocarbons already discovered but not yet developed [LINK]. So the question is: even if the new technologies are successful will they have a significant impact for operators? I suspect the answer is no.

New algorithms and systems may provide marginal gains around the edges of existing fields and provide additional in-fill development opportunities. They may reduce the number of people in G&G dept 10%. Commodification of techniques (as happened for 3D animation) may see the demise of some companies and job-roles. But I don’t think it’s going to provide a revolutionary impact. Of course, I may be wrong.

If I am right, this suggests that there will be two main opportunities for companies providing technology here – either to provide an “add-on” to the main interpretation platforms (Petrel, OpenWorks) and then sell small numbers of seats to operators in special circumstances, or attempt a wholescale assault to replace the platforms already in place. Neither of these are revolutionary for operators and result in minor cost reduction by pitting service company against service company.

I think the 4th industrial revolution is likely to provide only a small impact on the dynamics of this part of the value-chain. There may be a displacement of revenue from one software vendor to another, there may be some marginal in-fill development opportunities that will add more elasticity to oil supply (and help to further stabalise prices) but neither of those are going to be massive nor revolutionary. I think that the 4th Industrial Revolution gains have been captured already – AI, auto-pickers, attribute statistics, simulations, integration, cloud, geolocation, computing power in the hands of individuals – the main technologies are already in place. Gains from here-on-in will be marginal.

There is one thing that may change my view, however. If this happens it will have a profound impact and swing power towards the national resource owners. If these innovations are adopted at the level of the nation state things may change.

National Data Banks were established in the 1990’s (example LINK) to hold archives of seismic and well data and make them publicly available. These may get a boost.  Cloud technology and on-line AI-based mining-algorithms may change the way that license economics work by de-risking exploration and encouraging competition. If this is combined with a stable oil price there is a potential recipe for reduction in the incentives needed for exploration companies. That could change the economics and the structure of the discover, farm-down, refinance, develop and keep carried-interest process that is used today.

Automation Risk

We have recently seen some very high-profile failures of IT systems – whether by Cyber Attack (WannaCry and Varients [LINK]) or by poor operation risk control [LINK]. Something is wrong in the way things are managed

Insurance companies are starting wake up to their potentially unexpected liabilities around this risk [LINK]. They will certainly start to price this risk; this will mean that risk-reduction investment will have an immediate identifiable financial benefit. Perhaps it’s time to take a different approach

For years, I have railed against the distinction between “IT and the Business” [LINK]. I think the time has come for this gap to be finally put to rest. They are now truly inseparable.

Statoil has recently announced its response to the 4th Industrial Revolution (or Digitalisation). [LINK]. The most significant part of this is that the initiative is led by the COO. Of course it is!

If we were to take any other industrial process technology in Oil and Gas (say compressors) the management line looking after these runs up through the COO. There is not a Chief Compressor Officer who reports through the CFO and imposes compressor decisions (or delays) onto operations.

In that case, why would computerised operations technology report through the CFO via the CIO as is the case in many organisations. This should be part of the COO role. This recognises that IT is now central to operations. This is how it should be, because it is now at the heart of the current automation of operations [LINK].

In line with this I propose that the COO needs to own a new risk – Automation Risk. One of the advisors to the COO would be an Automation function – responsible for assessing and managing benefits and risks as well as defining policy across the organisation. Operational assets should comply with policy and work with Automation function around standards, risks and controls. Assurance functions can then audit compliance via the Chief Risk Officer – the right checks and balances would have saved a few hundred million dollars across the airlines in the last 12 months, perhaps a billion dollars across the industries hit by the WannaCry virus.

Automation risk planning means that the COO knows what risk sources there are that cause automation systems failure and what is the consequences of that failure would be. Importantly, he also knows what actions could be taken to reduce the likelihood and impact of a failure.

Then he can approve a business decision to choose which reduction measures are implemented. The COO must then know the real-time status of the mitigation measures – are they ready to work in case they are called upon and what is the current risk status of the organisation, is it acceptable and – if not – what is being done about it?

Contact me if you want to know about planning using Bow-Tie models and how you might be able to monitor current compliance in real-time, set-up alerts and manage your automation risk.

[Image credit: https://smlrgroup.com/universal-cyber-risk-model-part-1/ ]

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.