BA IT and my Eggs Florentine

So it happened again yesterday. This time BA cannot handle luggage. A bit of an issue for an airline. No word yet as to the cause [Link] but it did mean that checked baggage did not travel with BA passengers.

I took a risk and travelled BA this last weekend (I was using air-miles for a trip to Romania where I was helping out a friend with a project in the hinterlands there) and the experience was pretty reasonable but even I had problems. This time my probelms came from catering.

I flew in the business class cabin  (or as BA call it Club Class – hopefully not a reference to how they will quell any dissent).  In any case there was all this pomp and ceremony involving hot towels and a menu for breakfast as we took off. I was given the choice of Full English or Eggs Florentine. Printed on some stout card in a very grand font. Sounded lovely. There were only 8 passengers in the cabin. But they packed only 4 of each menu item. Zero redundancy. So as I was the last to be served, I didn’t have a choice. The menu should have read – you’ll get what’s left over out the two possibilities or go hungry, good luck. People only got a choice until 4 people had chosen one option, and then there is no longer a choice. So, as my Texan friends would say, that fancy menu was all “Hat and No Cattle”

It seems that catering, like IT, didn’t use risk management and uncertainty when designing their systems. This highlights the danger of over-assuming and the consequences of running at minimum cost with no redundancy. Redundancy, like insurance, can be seen in hind-sight as wasteful. Sometimes it’s called “over engineering” – but only if it wasn’t needed. If the laws of probability catch up with you, it is really a prudent investment.

Risk management has three elements:

  1. Identification of the Risk, what can cause them and what the consequences will be
  2. Taking prudent steps to reduce the probability that the risk will materialise
  3. Making preparations so that if the worst does happen the effects are mitigated

Giving BA the benefit of the doubt and assuming that they knew that their IT systems may fail, the baggage system may halt, and that they may run out of eggs florentine, then I have to assume that BA management now hate their passengers.

The consequence failure seems to be  inconveniencing passengers.

Probability of Failure: At no time did they take steps to reduce the likelihood of tripping their whole IT system by pulling out a plug [link] (perhaps they might have double ported UPS, or Duct Tape over the plug!) or running out of my choice of breakfast (by perhaps packing say 6 of each choice, rather than 4).

Consequence of Failure: Let’s just inconvenience everyone – was not mitigated either, it was just accepted with a shrug. Though to be fair baggage was re-routed and couriered and people were re-booked on flights. I got an extra Bloody Mary. But still feel that it would have been better to reduce the likelihood of failure, as the mitigation seemed to be the minimum anyone could expect – and may be a legal requirement (except the bloody Mary of course, which probably the EU would not mandate)

Good luck with preserving the premium pricing for your Brand BA.

In a future post, I’m going to argue that as operations now rely on IT to deliver (and even more so in the 4th Industrial Revolution) it’s quite wrong that much of IT comes under the purview of the CIO rather it should now be part of the remit of the COO. Risk management of operational IT should focus on putting barriers in place to interrupt the cause and consequence routes, using an operational function lens, not an IT one. I Bet that is going to cause some organisational “team work” issues when it comes to budget time.

 

 

4th Wave Value – Upstream Oil and Gas

I’ve been engaged in several discussions recently on the benefits (or otherwise) of the 4th Industrial revolution [link] applied to oil and gas. I’ve decided to write a couple of pieces on this topic so I can refer to them with clients.

Technologies driving the revolution

I accept the WEF identification of the following general technologies that underpin the revolution:

  1. Wide-spread sensing of information
  2. Increased computing power, predictive models leading to increased understanding
  3. Artificial Intelligence leading to:
    1. Automation of actions
    2. Optimisation of whole systems
  4. Distributed, additive manufacturing

Benefits from the revolution

What will be the outcome of the 4th Industrial Revolution for upstream if we are successful?  Well there can only be three fundamental differences that can be made – I think we’ll get a combination of these:

  1. Per unit cost reduction in produced barrels
  2. Increased safety for the people involved in operations
  3. Decreased impact on the environment from activities

Items 2 & 3 tend to be driven on a compliance basis and form the requirements for permission to operate granted to companies by society using various methods of regulation, consumer pressure and protest. For my purposes I’ll assume that these are utilities [link] and that we always want more when there is no increase in cost, and that we’re unlikely to cut spending or trade down. Therefore, any cost-neutral improvement will be adopted and spending will only increase when it is mandated.

Driving down production costs

I am going to concentrate on the cost per unit production. This comes from the cost of capital used to find and develop a field, the cost to operate facilities, and provisions for decommissioning at end of life. As the owner-operator of an oil field there are distinct supply chains for each of four phases of life:

  1. Exploring, Finding and Appraising deposits of oil;
  2. Planning, Designing, Building and commissioning facilities to extract and transport it to market;
  3. Operating the facilities; and
  4. End of life decommissioning, facility disposal and restoration of the environment

Benefits for exploration

In the initial phase of oil field life I would say that we’ve already captured many of the benefits. Wide spread sensing and large computing power would be a great description of what happens with Seismic data, Geoscience earth-modelling and directional drilling.  I am sure that if I looked at the number of people employed and unit-cost of discovery of a deposit I would see a much more efficient scenario than we did in 1980. The figures are somewhat distorted on a cost-per-barrel basis as we have been finding smaller deposits (a feature of geology rather than our abilities).

Benefits for Development and Projects

In the field development phase, we have seen some ingress of new technologies – ROV, Subsea completions, dynamic positioning of FPSO’s and such has led to economically possible concepts for some small or hard-to-reach fields that we’ve found. Field and facility performance is more accurately understood through simulations and we’ve seen some benefits to designers from the use of CAD systems. There is still scope for development to reduce the cost and errors associated with Engineering, Procurement, Construction and Commissioning. There are few real-time feed-back loops here, or analysis of project simulations. The management of large capital projects is still a mine-field of risk, change orders, document control, cost-overruns and schedule blow-out. These are caused by fluctuations in the real-world vs. plan with late in-flight adjustments. More accurate planning, contingency, dependency management, construction order, logistics, pre-commissioning maintenance, start-up etc. would provide benefits.

Benefits for Operations

The revolution should be able to affect operational optimisation the most, this is an area almost untouched by the revolution so far. An OIM on a field from 1980 would recognise a lot of the technology (if not the work-practices) used today. The exception to this is the wide-scale adoption of communication meaning that the split between on-shore and off-shore is far less.

It is possible to argue that the 4th wave has enabled the shale revolution and that the operating practices from this type of development are fundamentally different to conventional offshore and on-shore fields. The operating margins are smaller, decline curves more dramatic and the constant drill-complete-operate cycle has forced change.

I may be controversial but I’d say a lot of the operational work-practice changes seen in the North Sea have majored on reducing manning offshore and increasing the safety of operations. I believe that, despite the vast increases in potential data, the fundamental way that information is gathered and acted upon has not changed much.

When I walk into a remote operations centre I see a lot of people collaborating with each other, lots of excel spreadsheets, cameras and discussion. Integrated planning and turn around planning are still being done off-line and I don’t see visibility of supply, logistics or automatic optimisation of these functions.

There is a conundrum here of course. The facilities that are in operation (and those still being commissioned) are not designed to harness 4th wave opportunities so we have (at least) two problems. Firstly we must retro-fit new concepts into facilities that will be with us for the next 30 years, and secondly we need to influence design and development so that this retro-fitting is no longer needed in the future.

Benefits for de-commissioning

It’s early days on the decommissioning front. I suspect that for operators the benefits will show up through normal procurement cycles. The smart profits are likely to accrue to those that can operate quickly and safely. Examples of clever automated technology are emerging – such as the self-levelling rams that lift whole top-sides fitted to the Pioneering Spirit [Link]

Next steps

With the current climate in Oil and Gas we’re seeing an increased interest in how to transform the operational environment and supply chain to drive out OPEX cost (development and exploration are of course now sunk [link)

Now I’ve set the context I’ll start to explore how an operator, or service company, can start to participate in these changes – what an operations business case will look like, what skills and approaches will be needed, what approaches are stopping innovation and what the risks are.

(Image source : http://ohioline.osu.edu/factsheet/cdfs-sed-2 )

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/

 

 

Where’s the Delta?

On Sunday August 7th 2016 Delta airlines suffered an IT outage. Earlier in the summer SouthWest airlines suffered similar.

Delta cancelled at least 740 flights by Monday (I am sure there will be more) and Southwest cancelled 2,300 flights.  (Reference link , BBC link)

My calculation, at the bottom of the post, suggests that this cost DELTA at least 60 Million USD in lost capacity –  not counting the damage to the brand and additional costs associated with handling customer enquiries.

IT and the business are inseparable in the 4th industrial revolution. For many years there have been moves to outsource IT, drive down its cost and to make it standard and commoditised.  For utility IT this made sense. It was a cost of doing business. It was a necessary qualifier attribute but conveyed no competitive advantage.  If your copy of Microsoft Word was slightly faster than mine, it was unlikely that you’d capture more business or be able to charge more.

The outsourcing movement was used to drive this process, often awarding contracts to low-cost service centres in Eastern Europe or India.

In my view cloud based services – such as Microsoft 365 and Salesforce.com will become the norm for utility IT services and remove most of this responsibility from the IT department which will, as a consequence, go the way of the typing pool. In 25 years new entrants to the workforce will scratch their heads wondering what the point of the IT department was.

The world is, however, changing and changing rapidly. IT is becoming embedded into the core operational process of business. And executives that don’t understand IT will not succeed for long. Any company that perpetuates the phrase “IT and the Business” or any IT department that talks of “The Business” as if it were something separate from the IT function will go the way of the dinosaurs.

I don’t know if Delta outsourced its IT, or what the cause of the issue was. But it is clear that the situation was mismanaged before the outage (Reliability and resilience: no hot-backup, or hot disaster recovery ). This calls into question either the competence of those charged with planning operations or the business decision to not invest in technology and systems. Either way this is a failure of management to grasp the importance of IT in the primary operations of the business. Just because you don’t understand it doesn’t make it simple, or mean the problem can be ignored. Airlines are pretty good at maintaining aircraft, there are international standards for how it should be done and inspection audits making sure it is. Perhaps we need something similar for IT?

On this occasion it was a risk management failure where the loss of IT functionality impacted availability and utilisation of assets. My guess would be though that there are many areas where IT could be applied to the primary business to drive increases in efficiency and reliability. If management is unable to understand the business case or appoint competent management for IT resilience it is unlikely that they are exploring these more nuanced applications of IT.

The airline industry is not alone.

Put this into business context

In 2015 Delta operated an average of 5,400 flights per day, so about 15% of flights were grounded on Monday. Assuming that these planes were now in the wrong position some of them would have to reposition empty (let’s say 50%). Passengers rebooked who were scheduled to fly on a grounded flight (and Delta allowed all passengers to rebook any flight scheduled for Monday). Let’s say 30% of all Monday’s passengers (those on grounded flights and a similar number who took the precaution) took the place of fare paying passengers on later days.

Then we have a utilisation impact on aircraft of:

15% of one day capacity for cancellations

7.5% of one day capacity for repositioning

30% of one day capacity for rebooking.

52.5% of one-day’s capacity utilisation (in the height of busy season) was lost due to a systems outage.

Assuming 350 flying days this is then 0.525/350 = 0.15% capacity hit for this outage.

Last year’s revenue for Delta was 40Bln USD.

My “back of the envelope” calculation suggests that this systems outage cost DELTA $60Million USD in lost utilisation.

The brand has been impaired so future passenger numbers are likely to be lower than they would have been (at least for a while, especially as they could not even take bookings on Monday). Add to this the additional cost of media relations and customer complaint handling and we’re looking at a $100m problem.

Oh and if you are a European Union passenger you are entitled to 600 Euro’s in compensation too.

image credit Link

Let’s party like it’s 1993

It’s been a long time since I felt like I do now. 1993 to be precise.

In 1993 I was working in Paris with a ‘386 LCD screened laptop and had just loaded 40 3.5” diskettes to get Microsoft Visual C installed. Computing was difficult, slow and expensive then. Few people knew how things worked or what it could do.  Many of my bosses couldn’t work their email and none used spreadsheets. We may have used computers to desk-top publish but we still printed slides onto acetate to project them.

I was writing software for Schlumberger at the time. I was in Paris and working on Sun Microsystems boxes running X-Windows.

So why 1993 precisely?

I installed a programme called Mosaic. It was available on PC’s, Mac’s and Unix and you could download it from CERN in Switzerland using FTP, if you knew how. You could compile it using Gnu C, if you knew how. It connected to the network and let you do all sorts of clever things through WAIS, Gopher and HTTP, if you knew how.

My fellow engineers and I were blown away by the potential. It was obvious to us. When we showed this to our bosses back then they had no idea what the point of it was, how to use it or why it was important. And I couldn’t find the words to explain – there was such a gulf of understanding and so little time to fill in the blanks.

By 1997 Mosaic was Netscape and the internet boom got underway, I could buy a book from Amazon and have them send it to me in Norway and I had opened a US Brokerage account with a company called Etrade that you could access over a telnet connection to Compuserve. Now my bosses were intrigued, but still not investing. Investment in Linux version of our software and internet browsing didn’t start until 1999. Looking back that was quick, but at the time is seemed like an age.

I think about the changes that happened between 1993-2003  (just before the iPhone was launched), and the difference between 2003 and 2013 – how social media, location services and mobile internet have taken off. Life is very different now than it was 25 years ago, and it’s all driven from that set of technologies that Mosaic brought together.

Look at the difference at the productivity levels of geoscientist and data analysis with in Oil companies. That has tracked the changes in wider technology and information processing.

Now look at how little has changed in the operations of an oilfield since 1993.

Industry 4.0 feels like Mosaic did. It’s big, it’s going to be rapid and it’s going to change everything. Yet I still can’t find the words to explain it to the people I meet who are still struggling with their email. But I’m working on it.

Read this primer and perhaps you can help me explain to operations management:  https://bestemnetwork.com/2016/03/29/innovation-and-productivity-with-4th-industrial-revolution/

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]

 

 

ITF Aberdeen: Oil 2.5 vs. Industry 4.0

I was at the ITF Showcase in Aberdeen last week. It was an interesting event, if mildly concerning in some ways. Here is the link to the presentations [Link]. The encouraging notes were that there appeared to be some money being made available and that the industry had focussed on key themes around the MER UK forum [link]. Less encouragingly for me is the speed, energy and sense of urgency that was lacking.

I noted that the room consisted of 90% men (often in grey suits) and I reckon 75% were older than 50. So where are all the young people?

I have always been impressed with the approach of Colette Cohen [Link] from Centrica, a strong proponent of adopting technologies from other industries. Despite being a fully-fledged, dyed-in-the-wool oil and gas executive she retains an energy of purpose, nurturing of young people and a curiosity needed to drive innovation. She was on fine form and provided a welcome boost to the enthusiasm of the room while being the voice of reason when asked why wire-guided rockets couldn’t be tested on Centrica wells. Can we have more pioneers like her please?

I am based in London and the innovation and technology events I attend (and the informal networks I am part of here) feel very different. There is an energy and drive in the FinTech and internet sector that appears missing in Oil. Also when I go to events I find plenty of trendy young people brimming with ideas, and there are plenty of women there too (still not 50% but still way better than last week by a country mile). Diversity will be important for innovation. To be successful we must learn to harness the view-points that come from all sorts of diversity: racial, sexual, age, experience, industry, education – and find ways to encourage and shape ideas.

My next post is going to cover some thoughts on innovation, the fourth industrial revolution and what will drive productivity in the next 20 years. But suffice to say it will rely on data and automation, but many speakers [I’ll name no names] took great pleasure in informing the audience that they didn’t believe in the cloud and that they had piles of paper on their desk. When describing new tech there were plenty of references to “if you don’t understand this tech, then ask your kids”. It reminds me of ancient bankers who use fountain pens and a paper diary. It’s not cool it’s deliberately Luddite and crusty and an attitude that will kill our industry. Perhaps it’s time to get with the program or step aside.

One thing that stood out was the problem of accessing markets and testing new product. In my experience operators are generally not too interested in experimenting with new tech, and often their operating philosophy revolves around large frame contracts which means that they don’t really control access to the supply chain. The consolidation of suppliers, the integrated nature of their offerings and the point-nature of new technology development does appear to lead lock-outs and stifle innovation.

The Graph above is from Colette’s presentation. It’s an SPE graph, it shows that Oil and Gas has been great on innovation in the past, and we haven’t had a breakthrough for a while. What strikes me is that since 1946 all the innovation has been in finding or developing fields. My money is on operations and maintenance to join the party. And that will be driven by what the cool kids call “Industry 4.0” [link].

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Headline image Link

Digitally disrupted operations

I have already said that I believe the time is now for O&G operations to become digital. Radically different cost models are going to be needed and digital is one way they will be achieved.

“When assessing the implications, consider the fact that that new digital business models are the principal reason why just over half of the names of companies on the Fortune 500 have disappeared since the year 2000. And yet, we are only at the beginning of what the World Economic Forum calls the “Fourth Industrial Revolution,” characterized not only by mass adoption of digital technologies but by innovations in everything from energy to biosciences.” Pierre Nanterme – Accenture CEO [Link]

For me this revolution started with a computer programme called Mosaic, the first internet browser – which I discovered in 1993 while goofing around using Kermit, WAIS, Gopher, FTP and downloading cool stuff from GNU. I was being paid to generally muck-about and call it work. Since that moment I have witnessed a massive rise in computing power, information storage and interconnectivity that has left me gawping in awe. The chart below, from The New Machine Age, illustrates the trend.

Five Phases of Disruption

I model this disruption in 4 overlapping phases that are well established (each relying on the ones before it to progress) – and we’re about to see the fifth phase make itself felt.

Phase 1: Pure Information Industries

This was the first to be disrupted. It started with libraries, newspapers and advertising. As technology progressed this then disrupted industries requiring higher information capacity (bandwidth & storage) such as music and radio, and is now doing the same for television and cable companies. Bi-directional communication led to the X-Factor, the Huffington Post and any number of citizen journalists and bloggers.

Phase 2: Customer Engagement

As more people started to have access to and use the internet it was a small extension to make commercial transactions and shopping. As this ramped up customer experience of retail, customer-service departments and opened up access to a vast array of diverse products that could never be held in stock on the high-street. Now there are very few consumer engagements that do not have to integrate a digital channel into their offerings. Coffee and haircuts can’t be online – just about everything else can. Even there Starbucks is integrating a digital offering into their coffee order-to-pay process.

Phase 3: Co-ordination and logistics

It started with on-line parcel tracking, cross-docking and behind-the-scenes scheduling algorithms. Adding mobile GPS and mobile data allowed supply chain and logistics to start its transformation. Firstly on the containerisation and automatic freight and now down to warehouse location, stock control and soon perhaps delivery by dedicated drones [Link]. Phases 1, 2 & 3 have combined to give me my Occado delivery today at 12:30 (sharp).

Phase 4: Asset and resource sharing

This phase is still young and we’re seeing it play out in the consumer space first – a reversal I’ll elaborate on later. Companies like AirBNB, Uber, ZIPCar and others. In general this is the idea that Assets are not fully utilised by their owners all the time, and spare capacity can be made available through a brokering and booking service – and then scheduled and delivered.

Phase 5: Machine-optimised operations

Remote sensing, predictive algorithms, human-machine teaming – integrated with maintenance planning (plus all the attributes in phases 1-3) should lead to more reliable plant constantly optimised and operated by fewer people. This phase is being referred to as The Internet of Things.

“The Internet of Things (IoT) is changing manufacturing as we know it. Factories and plants that are connected to the Internet are more efficient, productive and smarter than their non-connected counterparts. In a marketplace where companies increasingly need to do whatever they can to survive, those that don’t take advantage of connectivity are lagging behind.”  Forbes Magazine [Link]

The reversing order of adoption

Sometime between 1992 and now a reversal in adoption sequence occurred. Prior to Mosaic the sequence of adoption was: Military, Big Business, Small Business, and Consumer. There was also a geographic sequence that meant technologies emerging in California took a few years (5+?) to make it to Europe and the same again to make it to Asia. The order has now reversed and the spread of ideas is both bi-directional and super-fast. For instance we’re going to see individuals install HIVE before most plant install remote operations. So I think we can already see the new technologies and ways-of working being successfully deployed for consumers – the question is how will the Oil and Gas industry adapt them for its use?

How could real-time sharing of Oil and Gas assets and equipment be made to work? How could we create an “Oil-Uber” for self-employed drilling engineers? How can we scale-up technology like HIVE, algorithms for maintenance diagnostics, combined with the GPS on a tag like that in my £100 Garmin watch attached to and despatch the most available uber-spare-part.

Of course, innovations will sneak up on us through lots, and lots, of small changes but the effect will dramatic – looking back we will see the change, but it will happen gradually with the companies that use more efficient technologies buying assets from those that don’t – or, more accurately, buying assets from their officially appointed receivers.

Crash of 2016 and rise of internet of things

As I write this post crude Oil is trading a shade under $30 and Iran is set to re-enter the market. When I was in Kuwait I thought that the ramp-up of Iraqi production would swing the market – I had not counted Shale or Iran. In some ways a price drop was inevitable in a cyclical industry but the effect of this drop is painful for many good friends in Aberdeen and Stavanger – and other oil-centric towns and cities around the world.

What will the up-shot of this price crash be? Perhaps there are lessons from history?

Price crash of 1986

The chart here (from the FT [Link]) – shows the oil price from 1983-88.

What changed after the crash of the mid-eighties? In my view, the most significant change in Upstream came in Exploration. New techniques and rapid advances in computing power reshaped whole departments of geologists, petrophysicists, geophysicists and started the movement towards integrated sub-surface modelling and simulation which we have today. What happened was a rapid reduction in finding costs and increases in certainty (pre-drilling) – leading to tools that provide deep understanding of deposits and accurate ways to manage reservoir dynamics.

This article in Computer World, May 1987 (page 89) [Link] is subtitled “Cost-cutting prompts Sohio to centralize and integrate systems” – this is the world I remember joining as PDP-11/34’s were being replaced by VAX 11/785 and Micro-Vax’s and sun microsystems 4/330’s, and if you didn’t know how to configure a Versatech plotter and UNIRAS libraries you weren’t much use. That was the start of, and without any research, I’d estimate that the cost on a job-by-job basis has fallen 90% and enabled far more technical reservoirs to be identified and quantified – leading to access to new territories, new financing mechanisms and new development concepts.

The imperative in this period was reservoir optimisation which quickly came to the fore with all manner of rapidly applied innovations in complex drilling, remote sensing and reservoir simulation. Exploration took a back seat for a while with lots of analysis and “banking” of reserves which were not really developed until the mid-noughties.

Price crash of 2015

So what’s going to happen this time around? Like 30 years ago I see that there will be a rush to take cost-reduction actions now, and there will be a period of reflection where new design patterns and new dominant designs will emerge ready for the next upswing.

Low-cost operational interventions

I think we will see the case for low-cost operational interventions. More temporary fixes for failing plant with minimum workable solutions applied to prolong life until shut-down (either permanent shut-down, or a large overhaul). This will include various forms of integrity management solutions – this might be an interesting year for companies like Wood Group, Intertek, ICR, AIBEL etc.

New design pattern for operations

Rapid cost reduction in the North Sea must now be centred on reducing operations costs. This means increasing the throughput of existing plant and reducing production-loss due to outages. This will mean accurate measurement and control, real-time plant-simulation and low-cost approaches to maintenance. Like we saw consolidation of exploration departments and the emergence of integrated geoscience teams we will see the rise of joint operations teams (concepts that have existed for a while but never fully had their impact). We will also see the rise of computer simulation and integration of data across domains – with predictive scheduling of parts and preparation of work-orders so that crews will be able to prioritise work and maximise the value generated from each shut-in period.

The impact of this will be a reduction in lower skilled workers and an increase in on-shore data-savvy planners. There will need to be more instrumentation and remote sensing, data communication and integrated dash-boarding of data. Emerging from this will be discovery of key, high-impact monitoring and intervention techniques and dominant designs for way-of-working will emerge. Much of this work will rely on enabling technology which closely resembles “The Internet of Things” [Link] [Link]

Unlike the many previous attempts at “field of the future” and “intelligent operations” – and a hundred other buzz-words – this time there is real imperative to make this change.

New dominant designs for development

After the 1986 price crash lots of back-office work was undertaken in exploration but drilling was at much lower levels for more than a decade. This time it’s going to be field development that takes the pause. According to the FT, WoodMac reports that over $400bln of projects are now delayed or cancelled. [Link]

I’ve talked to a number of operators this year and no-one is worried about designs taking longer. Everyone wants projects to cost less so that they can have a better chance of attaining FID. I predict that the dominant designs emerging from new design patterns and the remote sensing and operations will be incorporated into these designs in an integrated way. Taking asset data streams (and interpretation of them) into the integrity and barrier models from day one. This will lead to substantially lower cost operations.

With the retirement of the old-guard in both operations and development I expect to see younger engineers who embrace new technologies take major decisions. These are engineers that “get” the bigger picture and are frustrated by the pace of change. Their intervention will lead to more computerised monitoring, more adoption of technology like sub-sea processing, differing materials and techniques and wider acceptance of what were – five years ago – things not considered “proven” – or at least, not proven to the satisfaction of the old-guard.