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, 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.

It’s just an analogy

I’ve recently been working on analogies designed to let me talk about Industry 4.0 concepts. In short I’ve been trying to find ways to explain what’s almost unexplainable, and often to a sceptical audience. This is my current favourite:

Here’s what happened lasttime

In 1993 the Internet was explained in terms of bits, bytes, modems and tunnels. Most people had no idea why this geeky stuff would be important or what it could possibly be used for in everyday life. By 2003 it was explained in terms of Amazon and Facebook. Now my mum can order shopping on-line but has no idea how the Internet works. That’s how it should be, invisible to the application. My niece uses Facebook, WhatsApp and ASOS and can’t really imagine not using them – it’s woven into the fabric of how she does things, she’s never done it any other way. Why would she? In the mean-time those that had no idea what the geeky stuff could do ignored Amazon and are now closing their retail space [link]

Here’s what’s happening now

Industry 4.0 is now explained in terms like sensors, internet-of-things, and security. There is little understanding of how to retrofit this into existing ways of working, or why all this geeky stuff is relevant. In short people think this is a nice to have but really changes nothing. In ten years I will be explaining this in terms of its application and not how it is implemented. Industry 4.0 will be a forgotten concept and we’ll be talking about its various applications – like operating and maintaining according to equipment condition. In 20 years time a maintenance engineer (like my niece does with Facebook) will have no concept of why you would (or even could) operate equipment without on-line condition monitoring, system level surveillance, and connected “helper applications” that learn from global failure modes. Why would she?

But surely we’ve already been here?

I normally get an objection at this point along the lines of this:

“We’ve had digital oilfield for years, and it’s promised a lot, cost a lot and not delivered much – why will this be different, why should I think there will be a change.”

In my view, things no longer change incrementally when platforms become ubiquitous and costs tumble 1,000 times. They “take off”. That’s what’s occurring now. Add to these exponential technologies such as machine learning (which self-improve with time and experience) and t the stage is set for big breakthroughs.

Four companies: Facebook, Google (Maps +Waze), Uber, Amazon would be impossible without the widespread adoption of horizontal general technologies. They’re interdependent and co-ordinated rollouts enabled cross-platform co-innovation at the application level.

By the way – If you think these companies are just fluff : Google is worth 356Bln, Facebook 350Bln, Uber 62Bln and Amazon 250Bln. In total over a trillion dollars. For comparison Exxon is valued at 360 Bln.

Adoption Curve is reversed

Here’s another thought – In the 1960’s Military and Space applications were modified for business use before finding their way into the hands of rich consumers a couple of decades later. Facebook-like platforms and messaging applications such as Skype emerged first in the consumer space before being adapted for corporate deployment.

I think this mode of adoption is now true for application level innovation generally. If this is so for our next wave application innovation for industry 4.0, I expect to see it emerge first in the consumer space, deploy rapidly at scale and be ready to find ways to adapt and deploy in industry. It will be people like my niece that will know how to leverage these applications with no need to have any knowledge of how the underlying infrastructure works.

Keep your millennials close at hand; you’ll need their insights.

Image Credit http://parterre.com/2011/12/01/interrrupted-analogy/

 

 

Innovation and productivity with 4th Industrial Revolution

This is a long post. There is a lot to understand on this topic and this is the primer you’ll need. Please do follow the links. It will take a while but it’ll be worth it.

There is much being discussed around the acceleration of technology and how exponential development in multiple areas is converging and how this will impact on industrial production. About time too really because productivity is failing to pick-up, interest rates at or below zero, cash being hoarded by companies and investment rates are low [link]. This exponential increase is actually not that new – Moore’s law’s been around since… well since Moore launched Intel, and it was a one-way flow before even Schottky was on the scene. These trends are not new and if you don’t believe me here’s a great talk from 11 years ago by Ray Kurzweil with lots of evidence and predictions [Link]. Even Bill Gates saw this in a book he published in 1999 called Business @ the Speed of Thought [link], though these days that speed would be seen as a little too slow.

In my opinion the Oil industry harnessed many of the aspects of this movement in upstream exploration during the 1990’s. It was an early adopter in the process of FINDING reserves. Then the process of adoption stopped. Productivity per geoscientist and the complexity of the information they deal with is orders of magnitude better than it was during the last oil-bust of 1986, so much so that we now have more fields and deposits than we know what to do with. We’re pretty good at finding the stuff. But we’re quite rubbish at developing and operating it at low cost – especially small deposits, which we are so good at spotting now. Development, Operations & Maintenance has ossified – contracts and work practices are stuck. From an operator approach, the production of hydrocarbons has barely moved since the early 90’s (FPSO concepts aside). In my opinion through outsourcing, procurement, short-termism and misalignment of incentives it has become positively petrified.

If the Fourth Industrial Revolution is really going to have an impact we’ll need to address development on four fronts: Economic, Social, Political, and Technical

Economics

If this is going to happen then it has got to make sense for the bottom line. That means productivity: outputs, inputs and the cost of technology. McKinsey, recently cited in Industries of the Future, by Alec Ross [Link], suggested that the manufacturing sector could raise productivity by 2.5% to 5% and save more than $1Trillion in cost annually.

In one example McKinsey says “To capture the potential, manufacturers can consider three moves. Primarily, companies can gather more information and make better use of it. An oil-exploration company collected more than 30,000 pieces of data from each of its drilling rigs—yet 99 percent of that data was lost due to problems of data transmission, storage, and architecture. The tiny trickle of data it did capture was incredibly useful for managers. But so much more can be done. The executives we surveyed said that correcting these data inefficiencies should improve productivity by about 25 percent. [Link]”

Of course some traditional economists think we’re doomed to no innovation and permanent low growth – such as Robert Gordon [Link]. There are many in the old-guard of Oil and Gas that would agree. Most of them have their secretaries print their emails out for them, and refuse to carry a smart phone. Good luck chaps, I think you’ll find the millennials don’t care what you think anymore. Others say differently [Link]

There are many big hitters with some very big numbers, they’re all pointing in the same direction. I’m backing the future, not the past. And I think that Industry 4.0 will feature in the future of Oil and Gas. There are challenges but the prize is big enough that we will overcome them.

Social

The way that many of us work is going to have to change. Luckily the Millennials are already preparing for this shift with their search for meaningful work, emphasis on creativity and individuality; and understanding that they can blend their work and leisure time in ways that the crumbly generation see as slacking and entitled. Forbes have a top ten ways in which the work place will be influenced [Link] and Linda Grattan has her views here [Link]. For me it just seems an obvious way to work. But then I’ve never been very good at dealing with routine, structure and command-and-control. It’ll be interesting to see how we can blend the command-and-control requirements of operations with the caffeine fuelled micro-attention span of people even more “wired” than me.

We’re also seeing cyber-social developments such as the creative commons movement [Link] and open source projects like the Arduino [Link] all of which are fuelling exponential cross-fertilisation of ideas. We are witnessing the rise of the sharing economy [link] and temporary configurations of people who move about often. These are all challenging assumptions about ownership and permanence that are at odds with our current ownership-model for resources.

Political

The Guardian in Nov 2015 reported that ” this revolution could leave up to 35% of all workers in the UK, and 47% of those in the US, at risk of being displaced by technology over the next 20 years, according to Oxford University research cited in the report, with job losses likely to be concentrated at the bottom of the income scale.” [link]

With modern communications and the ability to mobilise quickly we’ve already seen massive changes in the way the people (or, in Greek, demos) interact with conventional democratic systems and capitalism. This is very thoughtful piece by Yanis Varoufakis the recently deposed Greek finance minister [link]. Whether that’s the Arab spring, so-called ISIS, Brexit, the mass-migration of populations or the astonishing rise of Donald Trump, things are getting decidedly odd in traditional politics. There’s a lot of complaint and not a lot of traditional power that can be exercised in public anymore [link]. Just take a look at the mass-mobilisation of a Brazilian flash-mob to protest graft allegations levied against the establishment [link]

Cyber-politics is a whole new dimension. Whether cyber aggression is aimed at accessing private information, denying or altering the dissemination of information or compromising the physical integrity of machine-based systems the ability of people to alter the course of events through “hacking” has never been so great. China has its infamous PLA unit 61398 [Link] one of over 20 cyber-military units it controls, North Korea doesn’t like Sony much as the 2014 hack showed [Link], Iran might be the land of the rising Shamoon that hit Aramco [Link], Ukraine has got on the wrong side of Russian Hackers who shut off their power grid [Link], and who knows who might have written Stuxnet that took out the Iranian centrifuges while telling the control room all was normal [Link]? Now the actors are not only nation-states, but also corporations and little boys alone in their bedrooms [link]

We have the Geneva convention that is supposed to stop states shooting the red cross, bombing civilians, gassing troops and firing mercury-filled dumb-dumbs. We have the international court in The Hague (funded by Andrew Carnegie incidentally [link]) that prosecutes war criminals. I’m not sure who I should call if North Korea invades my X-Box or steals my Bitcoins. And if you are a corporation with cross-border operations you don’t either.

Technical

There are a number of technologies that are developing exponentially at the moment and they’re feeding into changed ways-of-working that will bring about the fourth industrial revolution. Ultimately this will help you plan to build better plant and it will help you operate what you have better. Optimising operations is a sense-and-respond problem. Prepare for the future, know what’s going on right now and do things to make it better. Technology that helps falls into four areas that increase:

  • learning about what’s possible;
  • what’s going on right now and situational awareness;
  • knowledge of interdependence, decision options and consequence; and
  • ability to execute quickly and accurately

Increased learning about what is possible

Big data has gained traction in the last decade. Grab lots of data from everywhere, apply some Bayesian stats, set a base-level and determine the probability of correlation. Works really well when you buy a book from Amazon and it suggests that you might want to buy some reading glasses to go with it. Works pretty well in finding potential hidden relationships and developing predictive algorithms for equipment failure too [link] [link]

Like a lot of developments, this area is moving fast. How do you know what’s even possible these days? It’s so hard to keep up. Data overload, over-stimulation, who even has time to read this stuff?

I remember Schlumberger creating an amazing “portal” called the hub [link], Other companies did similar [link]. Initiatives were started to capture the learnings from each employee and make them available to all other employees. I even heard a talk once describing the use of retiree mentors to help existing employees [link]. People were planning for “The Big Crew Change” when the aging workers retire and new low people come on board [link]. This all tied into concepts like “Hive Minds” which were popular in the 90’s [link].

Well “The Big Crew Change” became the “The Big Layoff” when oil prices crashed in 2014. All that experience and knowledge was not on the balance sheet but was on the P&L. So it was fired without financial impairment and write-off. But the fundamental problem remained, and probably got worse. So much to know, so much to learn and no time to do it. Welcome to one of the drivers that will build demand for machine learning.

Machines can analyse masses of information much quicker than humans can. Up until recently, however, doing that in context and to derive meaning from them has been hard. Development has been showcased by game-playing computers such as Deep Blue for Chess [link], then Watson for Jeopardy [link], and most recently a Google built machine – AlphaGo for GO [Link].

Combine learning algorithms with connected systems, however, and things get really interesting. Learning requires teaching. Unlike programming in Fortran, learning machines construct their own programs by being taught and from the situations they encounter. Distributed and cloud-connected learning is exponential, one machine learns something somewhere and every other machine knows it. Forever. Perhaps we should blow the dust off those long-forgotten “portal” promises around knowledge bases, institutional learning and corporate memory?

Here is a great TED Talk on machine learning [link]. Of course it doesn’t always go well as Microsoft found out with it’s recent “Hitler loving Sex-Robot” [link]

What’s going on right now and situational awareness

Machines that learn what matters and suggest how to respond can eliminate operator overload by removing the trivial and hiding noise. Automated actions can be taken to keep things running. I recently heard an analogy about the difference between the information received by a pilot of a typhoon (arguably the worlds most advanced fighting machine) and a world-war 2 Spitfire. The Spitfire pilot had dials telling him the airspeed, engine speed etc. All just data. The Typhoon pilot, however, could not possibly cope with all the data available. So this data is assembled to show him only what he needs to know in the current situation and that depends on context.

Paul Smith, former UK RAF Pilot says “Bring all these [sensor and interpretation] elements together and it becomes clear why we talk about Eurofighter Typhoon operators having the ‘Combat Edge’ – the situational awareness and a suite of flexible weapons options that offer pilots a real advantage in the battlespace.” [Link]

Building on this, if the aircraft systems detect a heat-seeking missile closing, it launches flares automatically and tells the pilot afterwards – no point in raising an alarm and waiting! Same for the oil and gas sector, why do automatic fault development detection systems write a report and wait. Why don’t they just order the parts, consolidate shipments and schedule engineers for the next maintenance activity? It’s a small example but Amazon is already letting washing machines re-order soap powder [link], Imagine what Amazon-like logistics would do for the Oil and Gas industry.

In order to know what’s going on right now requires a lot of sensors talking to each other and reporting back. Too much detail for a human system to ever cope with properly. The data needs to be reporting to systems that learn what’s important, what actions it should take and how it should present its findings to its operators. The system needs to learn how to behave. These systems need to be aware of the situation and act accordingly. Cloud computing is also an important vector this mix, where systems are connected to each other through internet, and keep each other in synch sharing learning and preparing information so that it can be shared widely, securely and scalably. Google are letting developers play with their learning platform [link]. This is an area where we will see rapid innovation that Oil and Gas can benefit from.

Of course there are some very boring building blocks that will be needed. Connecting systems together will of course require a lot of plumbing – don’t underestimate the size of this problem, here is an example of the type of architecture you might need [link]. Companies like Eigen (www.eigen.co), Tibco (www.tibco.co.uk), BEA (www.bea.com) are active in this area. And it’s important that we really know that our data is correct – as in this case when a demolition crew targeted the wrong house and blamed it on google maps [Link]. So companies like datum360 (www.datum360.com) and Informatica (link).

Decision making & Interdependence

Knowing what’s going on is great, but what do you need to do to make your situation better? That’s the question that quickly arises once teams get sight of data and information in context. Firstly it’s important to know what the options could be – but also how choices in one system effect another.

Simulation is one of the keys to understanding the consequences of decisions – that’s why chess computers work out 100’s of moves ahead and choose the best one to use now. To simulate the decisions on a plant requires a digital model of the plant and its behaviour against which to run tests. The digital model is sometimes called a “Digital Twin” and this allows you to make a change or react to a fault condition and see what the knock-on consequences of selected actions will be in the future. This can be used to test options and optimise outcomes. Hit the model with a series of possible actions in an automated way and it’s possible to uncover the best sequence of actions and back-calculate why, rather than the normal forward progression. It’s very powerful – here are some articles discussing simulation of plant [link]

Integrated planning enables you to make a decision about sequencing events in such a way as to minimise down-time by running jobs in parallel within real-world constraints. This might mean being prepared and ready-to-act when an opportunity unexpectedly arises. Understanding system-wide effects is the key to getting this right, and with more complex interconnected systems with cross-ownership (like present in the UK sector of the North Sea) it not easy – and the owner stakes in oil fields can lead to misalignment of financial interests. Bain has a good article on integrated planning [link].

So far it seems that human + machine combination provides the best mix for solving problems. The creativity of the human is key and augmented decision making with rapid feed-back loops from simulation enables optimisation of decisions. From the first simple spreadsheets that appeared in business the testing of “what-if” scenarios has meant that we have been able to tune procedures across many areas of operations. The combination is not a new concept, here is a very relevant paper from Carnegie Mellon 1998 [link]

Increased speed and accuracy of execution

One of the issues that I’ve come across is the “precision” approach of some operators in the field. The best plans are of no use if they are not executed properly, if parts aren’t damaged and if the wrong parts were not fitted. It happens. Sometimes, of course, the instructions make no sense and the field have to modify them to make them work. That modification of instruction is rarely fed back into the system so little learning takes place. Sometimes the plant is updated and records not updated. All this leads to mismatch between what is recorded and what the plant operators “know”.

Sometimes the physical effort required to perform an inspection means that it cannot be done as often as you’d like, or perhaps is skipped by a crew unwilling or unable to schedule. Autonomous vehicles are in use for inspection activities firstly replacing deep divers and latterly, as costs have gone down they are found in inspections roles as Drones taking cameras into inaccessible places. Perhaps it won’t be long until we have small UAV’s mapping plant and equipment in huge detail. Here is a TED talk that demonstrates what’s already possible [link]

On-site machining of parts may soon be replaced by on-site manufacturing. Additive manufacturing (a broader term than 3D printing) is finding its way not only into printing of small intricate parts but emerging are the start of large-scale construction. It’s not there yet, but imagine what this would mean for logistics or construction in hostile environments. Here is an example of a team in Amsterdam who are in the process of printing a Steel bridge over a canal. That could change some of our approaches to Maintenance and Modification one day. [link]

And, of course, there will always be people involved. But multi-skilled and informed. Augmented reality displays – identifying parts, performing on-the-fly risk assessments and acting as advisors. This will change the way that operators will be able to apply basic skills augmented with real-time instruction and feedback. Meron Gribetz demonstrates here a virtual reality system that could revolutionise the on-shore-off-shore interface, as well as providing just-in-time information. Here is his TED talk [link]

And if you don’t think a Robot can replace people on platforms – have a look at this [link]

 

 

Schumpter’s Cayman Island holiday

Schumpter was an economist who theorised on the creative destruction of capital, replacing activity in old industries with activity in new ones. I’m not an economist, but to me it is an interesting time now because it all seems to be a bit broken – the oil industry is being knocked down by external (temporary) market distortions and governments are unable to enact public policies that might help because they don’t have access to the tax base they once had – and have been busy expanding the spending of what they do have on other things.

Today’s FT was a classic issue – with stories exploring some hot topics:

Accelerated Decommissioning in an article titled – “North Sea fields face end of production” [Link]

A piece examining the dynamics of adjusting to low oil prices – “Oil Producers retool for lower prices” [link]

A call for support and regulatory intervention into the North Sea shared infrastructure – “Premier Oil urges action to maintain North Sea fields” [link]

A story about BP’s accounting profit – “BP Shares tumble after $2.2Bn fourth-quarter loss” [link]

The WoodMac analysis says that 50 North Sea fields could cease production this year. Of course they will need to apply for COP (Cessation of Production) agreement from the government:

Prior to permanently ceasing production from a field, Licensees will have to satisfy the department that all economic development opportunities have been pursued. To ensure that all issues are addressed thoroughly before agreement to CoP is required [link].

The article goes on to speculate that some of the lost revenues for exploration service companies might be replaced by decommissioning revenues. While this might be true on an aggregate revenue basis, it’s unlikely that you can use a seismic survey vessel in this process so there will be capital assets that become worth a lot less, even if employment has some life-lines.

The dynamics of low price adjustments are explored by Amrita Sen and Virendra Chauhan from Energy Aspects [link] – they make a great point that one of the cause of high costs in the last up-cycle was shortage of skilled labour (sometimes referred to as the big crew change [link] ). Many of the current workforce (upwards of 250,000 people [link]) have been laid off and many will leave the industry permanently. This may set-up a cost-dynamic that will increase input prices and damp capacity for the inevitable upturn, potentially leading to even larger commodity price spikes and surges in service company profits?

The call from Tony Durrant, Premier CEO asking the regulator to step in to protect shared infrastructure in the North Sea is one that I’ve supported on this site for a while. It’s not just power that they need (the CoP mechanism may already mean they have it) it is one of public policy, subsidy and – ultimately – courage. We saw David Cameron promise £250m to Aberdeen (aiming it in entirely the wrong direction). But that is really small potatoes, which – to mix a metaphor, and pay homage to John Major – will butter no parsnips.

This is not really subsidising or investing in infrastructure: For instance if we look at Indonesia:

The government’s plan includes constructing power plants that would supply 20,000 megawatts of electricity in the next 10 years and 1,095 kilometers of new toll roads to move goods faster across the vast archipelago. The projects will be concentrated in six “economic corridors” or growth centers: Sumatra, Java, Kalimantan, Sulawesi, Bali-Nusa Tenggara, and Papua- Maluku. The price tag: $150 billion over the next five years. But the government can only finance 30 percent of the cost; the rest would have to come from the private sector. [link]

If we look at Cross-Rail, a train to move people slightly faster from Maidenhead to Lewisham has a budget of around £15Bn [link] (which is 60x the subsidy for the North Sea)

In the 1970’s the Oil industry was seen as a way of providing tax revenues to the UK – you might argue that much of the Thatcher-era economic achievement was predicated on Britain becoming a net exporter of oil which, combined with the sell-off state industries, increased the tax take and enabled the unwinding of the debt accumulated by previous governments.

Most people don’t realise that Oil companies don’t pay just normal corporation tax – PRT is charged on “super-profits” arising from the exploitation of oil and gas in the UK and the UK’s continental shelf. After certain allowances, PRT is charged at a rate of 50% (falling to 35% from 1 Jan 2016) on profits from oil extraction. PRT is charged by reference to individual oil and gas fields, so the costs related to developing and running one field cannot be set off against the profits generated by another field. PRT was abolished on 16 March 1993 for all fields given development consent on or after that date. [Link]

Corporation tax supplementary charge manual here [link]

It’s perhaps as well that these sort of measures are in place because Oil companies (and service companies) are very well practiced in the art of reducing corporation tax – either by legitimately moving costs to high tax areas and profits to low-tax ones, or by – as BP has done today – booking as big a loss as they can (when it’s expected – a practice called “taking a bath”). They do this to provide a shield for future profits against tax. A practice similar to that used by the banks to shield their current earnings from the losses of the financial crash of 2008 [link]. Many of today’s tax “dodges” have been heavily utilised by our industry.

We’re seeing a situation where an industry (one of our few industrial and engineering success stories of scale left in the UK) being decimated by a temporary market swing and there is nothing that the government can do about it because the new industries which are very profitable pay little tax and where disruptive industries are supported by the “subsidy” from investor’s tax free cash piles sitting offshore.

Take for example UBER and it’s disruption of local tax-optimising (sorry mate only cash) taxi drivers:

A recent article in The Information, a tech news site, suggests that during the first three quarters of 2015 Uber lost $1.7bn while booking $1.2bn in revenue. The company has so much money that, in at least some North American locations, it has been offering rides at rates so low that they didn’t even cover the combined cost of fuel and vehicle depreciation.

An obvious but rarely asked question is: whose cash is Uber burning? With investors like Google, Amazon’s Jeff Bezos and Goldman Sachs behind it, Uber is a perfect example of a company whose global expansion has been facilitated by the inability of governments to tax profits made by hi-tech and financial giants.

To put it bluntly: the reason why Uber has so much cash is because, well, governments no longer do. Instead, this money is parked in the offshore accounts of Silicon Valley and Wall Street firms. Look at Apple, which has recently announced that it sits on $200bn of potentially taxable overseas cash, or Facebook, which has just posted record profits of $3.69bn for 2015.

[Link]

Interesting times indeed.

Subsidy on the agenda?

Last year I suggested that there were strategic reasons to maintain North Sea production. The system of interconnected assets and their cross-reliance on each other means that it will be in the common good for “UK PLC” to maintain key infrastructure despite it being a poor proposition for individual operators.

For goodness sake – we subsidise the tracks that our trains run on, I can’t see any argument for the creation of economic value there that does not apply to our North Sea processing and export network. [Link]

So I was heartened to see that David Cameron is in Aberdeen with what the FT called an emergency investment package. I was less pleased to see what the promised £250m investment was to be spent on:

The prime minister will promise a new “oil and gas technology centre” in Aberdeen to fund future research, including into innovative ways to extract oil and gas.

The package will also help expand the harbour and support the city’s pharmaceutical and agri-food industries to try to help Aberdeen diversify from its reliance on oil and gas. [Link]

Well that’s not exactly the response I was thinking about – seems to be a rather poor investment case for UK PLC. Luckily we’ve formed another task force.

His visit coincides with the first meeting of a new task force of senior ministers set up to deal with the issue, chaired by Amber Rudd, energy secretary. The group will include Anna Soubry, business minister, and David Mundell, the Scotland secretary.

Together with the OGA there seems to be plenty of civil servants looking at the issue.

True to form – the FT actually got to the nub of the issue with its parting shot:

Many in the industry are also urging George Osborne, the chancellor, to relax the rules around who pays to decommission oil platforms when they reach the end of their lifespan. Many argue that the strict laws making anybody who has ever owned a particular platform potentially liable for its eventual dismantling are discouraging companies from buying up ageing assets and investing in them.

One energy banker said: “One of the things that could really help is if we see more takeover activity, with companies buying either struggling rivals or older rigs.”But the main thing stopping that right now is that nobody wants to take on potentially massive decommissioning liabilities.”

The BBC covers his visit here [Link]

Despite the decline in oil prices there is risk capital available but to take this opportunity irequires a few critical pivots. They are:

  1. Decommissioning liabilities stopping the trade in assets to lower-cost operators
  2. Un-certainty surrounding enabling infrastructure operated by others
  3. Mis-alignment of interests between partners meaning operating committees stopping development plans

Perhaps rather than expanding Aberdeen Harbour we could change the rules and use this £250m to help sort these out? At least it would be a start.

What do you think, is the proposed disbursement the best use of the money?