February 26, 2018

The Big Crew has left the building, where do we go for help now?


I can remember, in the early part of my career, the value of a mentor.  Bruce was great.  I can't tell you how much I learned from that guy.  From technology that I didn't see in college, to how to use the file room, to how to prepare for a presentation to management, his guiding hand set me on a road for a successful career.  I tried to "pay forward" that gift when I became the old white-haired veteran and the next generation had become the ones asking all the questions.

Turnover from one generation to the next is a normal part of any workforce planning scheme.  It shouldn't be a surprise, or a crisis.  These generational turnovers, however, are exacerbated in the oil and gas industry due to the unfortunate alignment of recruiting and oil prices.


The Oil & Gas generation gap


The commodity nature of oil & gas prices creates periods of growth when prices are high and money flows to many projects including recruiting, training and the adoption of new technology.  Everyone rides the rising price curve up, from prospective employees who pick up on these signals and want to join the industry to academics who pick up the signal and increase their student enrollment.  Then, falling prices cause the house of cards to collapse; companies cut costs, including recruiting, training and the adoption of new technology.

These price-related decisions make their mark on the demographics of the industry.  The low-price cycle over the past several years is happening at a time when the Big Crew -- those like me who entered the industry on a high price note in the 1970s and 1980s -- are reaching retirement.  Just behind them is a gap in the workforce demographics left by lower hiring in the low oil price era of the 1990s, leaving a significant hole between the 30 year+ veteran planning his retirement party and the ten-year (or less) professional getting ready to take his place.  A well-ordered transition, it is not.  On the horizon is yet another gap that has already started to emerge with lower recruiting targets being set today by most companies worrying more about operating and G&A costs than future workforce requirements.


Where will the new professionals of today go for answers when the experienced domain experts have left the building?


Continuity of knowledge becomes challenging as the Big Crew takes with it not only power in numbers but also years' worth of expertise.  Companies can bring back their old experts as consultants or they can fill in specific gaps with other contractors or oilfield service company hands.  But many times, the external consultants really don't have the expertise or context they need, and the oilfield service companies have the same Big Crew Change problem that the operators have.

The experts of my generation are more than willing to mentor young professionals, but often there is a communication style gap.  My generation learned either from the classroom model (which always favors the instructor over the student) or from the one-on-one mentor model, where you have to pin down the expert (often in a bar at a professional conference) and ask the right questions.  They also built expertise over time and through trial-and-error, which lets them synthesize data from various sources to fully analyze a situation.


Can technology fill this "expertise" and "experience" gap?


A number of Oil & Gas companies have experimented with knowledge management tools to help "capture" best practices and make them available to the next generation of workers.  Largely, these efforts have been less than successful.  The problem of documenting a best practice into a structured database has proven to be a difficult one, as well.

The same experts who would readily mentor an up-and-coming engineer or operator see their willingness turn to hostility or frustration when asked to document his or her career-spanning learnings for input into some kind of new technology.  Other interviewing or storytelling techniques are easier on the old expert, but are more difficult to parse out of the next-generation audience.


Can technology replace human learning?


For me, the problem is this: how to "document" expertise and, then, how to make it easy to access in a form that fits the needs of the next generation. If I were asked to participate in the design thinking session for a new knowledge management system, I would frame the problem in three parts:

1) Definition of the knowledge problem scope

2) Description of the best practice process

3) Capture of the results (to demonstrated superior results) and share in a format that can easily be consumed (like a virtual game or a YouTube like video)

Here is one example to illustrate:

1) The problem statement: Identifying zones where drilling might encounter a stuck pipe risk in drilling a complex well

2) What data do you need: What mud weights were used, where was the last casing set, what is the drill string size, what as the weight on bit, what kind of bit was used, what was the differential pressure between the formation and mud weight, was this pressure event predicted by seismic attribute analysis, etc.

3) What was the superior result that makes this a best practice candidate: The drilling contractor drilled through the under/over pressured zone without getting stuck and with little NPT (non-productive time).  


How do you embed this knowledge event "pattern" in the well design and well control technology and in the training material for new drilling engineers?


One critical issue is where the information is stored that makes up this "knowledge event."  It will probably be in many sources.  Defining the "meta" data from the "knowledge event" is key to creating an algorithm that would be scalable to other problems.  Drilling systems, production systems, subsurface systems will all contribute, so the knowledge event algorithm has to "crawl" these systems looking for the right events, assemble the data, identify the patterns (including the poor practices that lead to poor results, e.g. getting the bit or drill string stuck) and develop that knowledge asset.  Then, you need to find the "broadcast" mechanism to alert others the next time this situation shows up (both in the design on the next well, and in drilling the next well).


Is emerging technology the solution?


Maybe emerging technology and automation will reduce the workforce requirements for oil and gas operators and service companies in the future. But, for my money, expertise and best practices will always be valuable, even if it only supervises learning for the new AI algorithm or robot. Understanding how to capture knowledge and distribute it effectively is a critical challenge, especially as the current experienced workforce leaves. The industry has probably started a little late to face this challenge but there is no better time to start than now.

December 11, 2017

Too Many Choices

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August 22, 2017

Slow Motion Data Crisis

Most of us respond to an alarm pretty quickly. A smoke alarm in your house, fire alarm in a mall, lightning alarm on the soccer field, or a tornado alarm or siren. We take these alarms seriously and get everyone to a safe place as fast as we can.

There are, however, other kinds of alarms we tend to ignore allowing a crisis to creep up on us. Let's call these slow-motion crises. These work along the same premise as the old Cajun story of how to cook a frog. The best way to cook one is to put the frog in a pot of cool water and turn up the temperature slowly so that the frog gets used to the rising temperature until it's too late. Turn the temperature up too quickly and the frog realizes his situation and jumps out. Sadly, we are the frog in this metaphor.

Businesses have alarms for almost everything. Operations boasts the ones we ordinarily think of - high pressure, low pressure, or failed systems alerts triggered by SCADA systems. However, one could consider the corporate monthly, or even weekly, management dashboard reports, where there are alarms for key metrics that impact the profitability of your business. Field personnel and corporate executives take these alarms seriously and do something to get to a safe (or profitable) place as fast as they can.

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August 2, 2017

Imagine Shopping for Your Data...

People enjoy the convenience of shopping online, which is more than you can say for most employees of large companies trying to find the data they need to do their jobs. Maybe what companies need is an online data marketplace? Can shopping at Amazon provide us some lessons on how to manage the Big Data environments we have and show us how to give an enjoyable "data" shopping experience for our employees?

I think I can safely assume that most people reading this article have experienced shopping on Amazon.com. Whether you were looking for a good book or something else, Amazon is a popular "place" (if I can use that term). Amazon began as a virtual book store and diversified, expanded and disrupted retail sales channels.  Visitors to the Amazon site will account for about 7% of North American retail sales in 2018, (versus 10.6% for Walmart - the largest brick-and-mortar retailer). Part of this can be attributed to 1.8 million items Amazon offers vs Walmart SuperCenter range of 120,000 average. Amazon also produces consumer electronics and cloud infrastructure services (IaaS and PaaS) and recently purchased Whole Foods (for $13.4 billion) to expand their grocery business.

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June 30, 2017

Summoning the Demon

Recently, we published an article on the "AI Coworker". Thanks for all your views. We talked about the role that "Buddy" might play in operations to increase productivity in the field and decision support center analysts to make sense of all the data that is being generated, and get a jump on predictive decisions that could create more value out of your existing assets. It sounds like a great opportunity to integrate human experience with artificial intelligence, but there are a few challenges along the way that we will discuss in this article. Will artificial intelligence take over in a digital world putting humans to the side? Will "Buddy" be a valuable partner, or will AI be considered "our biggest existential threat" as the entrepreneur, Elon Musk, said as he compared the research under way equivalent to "summoning the demon."

Warnings about the potential impact of artificial intelligence have recently been discussed by prominent business and technology leaders. Some warn the technology will destroy jobs while others point to ways it will create new jobs. In December 2014, in an article for the BBC, Professor Stephen Hawking said, "the development of full artificial intelligence could spell the end of the human race." Hawking goes on to summarize that artificial intelligence "would take off on its own and re-design itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn't compete and would be superseded." 

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June 13, 2017

AI Coworker

With everyone talking about Big Data, Advanced Analytics and the Industrial Internet of Things, I have been trying to look beyond the hype, think about what's next and the adoption challenges all this brings. These new technologies are coming at a time when the oil and gas industry is trying to see if it is safe to lift their heads out of the bunker they have been in for the last several years due to low commodity prices. Some, especially those invested in unconventional plays in the Permian Basin, have already left the bunker and are charging ahead with lease acquisitions, mergers and new drilling programs. Oil production is going up, inventories are going up, more pipelines are getting built, oil field service rates are rising on higher demand, but their prices are staying down.

Others are more cautious and many are still trying to "fix" their asset portfolios, selling properties to repay debt, (many majors reducing downstream assets for a few examples), cutting capital budgets and projects from their annual plans, leaning on suppliers to keep prices low and some are even trimming staff a little more. Exploration is down and close attention to the operating budget is still essential.

But the technology advances are not waiting for commodity prices to rebound. The cry for digitization and new business models ring from consultants' speeches at every conference. Are we looking at these new technology advances in the right way? Are they just new and more capable tools or is there another way to think about adoption and transformation?

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June 2, 2017

Battle for the Digital Core

While no one is popping corks on the champagne yet, things are looking a little better in the oil patch these days. Oil prices have recovered to a range between the mid $40s to the low $50s. Drilling and production costs in some basins have fallen to the point where $50 oil can mean a positive cash flow again. The Permian Basin looks healthy with lease prices in the best trends near $60K per acre, and increased drilling activity has added hundreds of drill rigs to the fleet over the past few months. OPEC has announced a production cut of over a million barrels of oil per day and crude oil inventories have fallen a little. A few major capital projects have been approved including:

·         Chevron's Tengiz Future Growth Project (Caspian Basin)

·         Statoil's, Johan Sverdrup (Norwegian North Sea)

·         BP's Mad Dog 2 (Gulf of Mexico)

·         Eni's Zohr (offshore Egypt)

This appears to be a sign we have reached the bottom of the commodity cycle and can start planning for better times.

I am not brave enough to try and predict future oil or natural gas prices or even global demand for fossil fuels, but I do want to talk about some of the interesting new developments in the digitization world that apply to our industry. I want to introduce a concept I call "the battle for the digital core." If the industry is preparing for new investments, investing in data as an enterprise asset and integration capabilities to help each employee become a more productive and better data analyst can have profound, long-term returns.

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February 23, 2017

Operational Technology (OT) vs. Information Technology (IT)

One of the many themes coming out of new digital technologies is the concept of operations technology or OT. This theme is more than just a new suite of technologies, sensors and smart equipment, but a different paradigm coming more from the world of control systems and field automation rather than from corporate IT. How will these new developments and the new data coming from field instrumentation fit into the world of digital data defined by IT and structured data management practices?

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February 1, 2017

In Defense of Silos

The Oil and Gas industry is frequently criticized as being a slow adopter of new technology and of innovations proven in related industries. We are also criticized as an industry that works in our functional and geographic silos and are reluctant to share data. This laggard behavior (we don't like that term and suggest we are "fast-followers") and our parochial behavior (we don't like this term either and would replace it with the term "functional excellence") around data and technology often creates barriers to information sharing. Data integration and even information protection are often late add-ons creating a complex architecture behind our firewalls.

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January 12, 2017

The Digital Disruption of Corporate IT

Is corporate IT in jeopardy of digital disruption? What does that even mean? If you read the latest doomsday warnings in articles by management consultants and technology vendors, there are constant references to the impact of emerging digital technologies on mainstream business models. They coined the term "digital disruption" and use the case histories of Amazon®, Uber®, Airbnb®, Travelocity® and others to warn executives of traditional brick and mortar firms to watch their digital backs for unconventional competitors.

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