Tag Archives: Digital oil field

The Way To Maximize Value from M&A Assets

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In North America, the only constant when it comes to Oil and Gas companies is change.  With mergers and acquisitions (M&A), hydrocarbon assets constantly change hands. The value of acquired assets will then either be maintained, increased. decreased or maximized depending on how it is managed under the new owners. It is generally agreed the value can only be maximized when the asset’s geological models, reservoirs’ dynamics, and wells’ behavior are fully understood to their minute details. The new owner takes over the asset but is not guaranteed the people with the knowledge.

Building a clear understanding of the new asset becomes an urgent matter for the new owner.  This understanding is typically hidden under the mountain of data and files that change hands together with the asset. How and when the data is migrated to the new organization, therefore, can build up or bring down the value.

Typically, when an asset changes hands, the field staff remains, but the geologists and geoscientists that strategized the assets’ management may not follow the asset. This can mean that a great deal of knowledge is potentially lost in transition. This makes the data and documents that are delivered, after the transaction is complete, that much more important to understanding the details of the acquisition. Obtaining as much of this data as possible is crucial.  As a geologist who has been through multiple mergers put it:

“Knowledge like drilling through a fault is only known to the asset team operating the asset. This information is not publicly available. During the transition, getting any maps or reports from the geologists will help the acquiring company develop the right models and strategies to increase value. We want all the data we can get our hands on.”

Another key consideration is software licenses and versions, which may or may not transfer.  We find that the risk of losing the information permanently due to software incompatibility, licensing, or structure issues is very real. Migrating the technical data during the transitioning period will help protect the new owner from data loss.

Per Harvey Orth, a geophysicist and former CIO who has been through three mergers and acquisitions:

“In many cases, companies made an agreement with the software vendor to maintain a read-only copy of all the data; just in case they needed to extract some data they had not loaded into their production systems (for the new owner) or need the data for legal or tax reasons later (for the seller). In fact, keeping a read-only copy can be easily negotiated within a purchase agreement if you are divesting an asset. When acquiring, then everything and anything you can get your hands on can be essential to getting the most value from the field and should be migrated. ”

Tips to Protect the Value of New Assets 

Experts like us can help ensure that data is migrated quickly and efficiently and that the right data is obtained from the acquisition target. However, if inclined to manage the data transfer yourself, we share the following tips:

Make it Manageable, Prioritize it Right:

While all of the data and information is important, time is of the essence. Most companies will prioritize migrating “accounting” data, and rightly so, but to maximize value, technical data must also be at the top of the priority list. The following should top your priority list: production volumes and pressure data, land and lease data, well construction & intervention data (drilling, completions, and intervention history), Reservoir characterization (logs, paraphysics, core …etc.)

Do Due Diligence with a Master List

Getting your hands on all the data starts with a master list of all the assets,  including such things as active wells and their statuses. This list is the first-stop shop for every department that needs to build its knowledge and processes to manage the new assets. It is also the checklist against which to assess received information. If you have invested in a MDM (Master Data Management) system, then adding the new assets to the database should be one of your first steps.

Know What is Good Quality and What Is Not.

One of the biggest obstacles that companies face is the realization that their own data is not standardized and clean.  So now they are faced with the prospect of adding bad to bad.

Much can be said about investing in data quality standards and governance practice. It makes folding in any new assets easier, faster and cost effective. If you don’t have strong data standards yet, see if you can inherit them from the selling company,  or alternatively get help from IM experts to create these standards and merge legacy data with the new acquisitions.

Make it Findable: Tag Your Electronic files

Documents like geological maps, logs, lab reports, management presentations, and other files contain a wealth of information. Finding the right file can take considerable time, especially if the organizer was not you. Take advantage of Artificial Intelligence and “tag” the files based on their content. This will create a layer of metadata and make finding the right file based on “petroleum natural language” easier.

For additional information or a free consultation on migrating M&A data please contact us at info@certisinc.com

Part 3 of 3: Are we progressing? Oil & Gas Data Management Journey the 2000s

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The 1990’s shopping spree for applications produced a spaghetti of links between databases and applications while also chipping away the petro professional’s effective time with manual data entry. Then, a wave of mega M&As hit the industry in late 90s early part of the 2000s.

Mega M&As (mergers and acquisitions) continued into the first part of the 2000s, bringing with them—at least for those on the acquiring side – a new level of data management complexity.

With mega M&As, the acquiring companies inherit more databases and systems, and many physical boxes upon boxes of data. This influx of information proved to be too much at the outset and companies struggled – and continue to struggle – to check the quality of the technical data they’d inherited. Unknown at the time, the data quality issues present at the outset of these M&As would have lasting effects on current and future data management efforts. In some cases it gave rise to law suites that were settled in millions of dollars. 

Early 2000s

Companies started to experiment with the Internet.  At that time, that meant experimenting with simple reporting and limited intelligence on the intranet.  Reports were still mostly distributed via email attachments and/or posted in a centralized network folder.

I am convinced that it was the Internet that  necessitated cleaning technical data and key header information for two reasons: 1) Web reports forced the integration between systems as business users wanted data from multiple silo databases on one page. Often times than not, real-time integration could not be realized without cleaning the data first 2)  Reports on the web linked directly to databases exposed more “holes” and multiple “versions for the same data”;  it revealed how necessary it was to have only ONE VERSION of information, and that  had better be the truth.

The majors were further ahead but for many other E&P companies, Engineers were still integrating technical information manually, taking a day or more to get a complete view and understanding of their wells, excel was the tool moslty. Theoretically, with these new technologies, it should be possible to automate and instantaneously give a 360 degree-view of a well, field, basin and what have you. However, in practice it was a different story because of poor data quality.  Many companies started data cleaning projects, some efforts were massive, in tens of millions of dollars, and involved merging systems from many past acquisitions.

In the USA, in addition to the internet, the collapse of Enron in October 2001 and the Sarbanes–Oxley Act enacted in July 30, 2002, forced publicly traded oil and gas companies to document and get better transparency into operations and finances. Data management professionals were busy implementing their understanding of SOX in the USA. This required tightener definitions and processes around data.

Mid 2000s

By mid-2000s, many companies started looking into data governance. Sustaining data quality was now in the forefront.  The need for both sustainable quality data and data integration gave rise to Well Master Data Management initiatives. Projects on well hierarchy, data definitions, data standards, data processes and more were all evolving around reporting and data cleaning projects. Each company working on its own standards, sharing success stories from time to time.  Energetics, PPDM and DAMA organizations came in handy but not fully relied on.

Late 2000s

When working on sustaining data quality, one runs into the much-debated subject of who owns the data?  While for years, the IT department tried to lead the “data management” efforts, they were not fit to clean technical oil and gas data alone; they needed heavy support from the business. However the engineers and geoscientists did not feel it was their priority to clean “company-wide” data.

CIOs and CEOs started realizing that separating data from systems is a better proposition for E&P.  Data lives forever while systems come and go. We started seeing a movement towards a data management department, separate and independent from IT, but working close together. Few majors made this move in mid 2000s with good success stories others are started in late 2000s. First by having a Data Management Manager reporting to the CIO (and maybe dotted line to report to a business VP) then reporting directly to the business.

Who would staff a separate data management department?  You guessed it; resources came from both the business and IT.  In the past each department or asset had its own team of technical assistants “Techs” who would support their data needs (purchase, clean, load, massage…etc.) Now many companies are seeing a consolidation of “Techs” in one data management department supporting many departments.

Depending on how the DM department is run, this can be a powerful model if it is truly run as a service organization with the matching sense of urgency that E&P operations see. In my opinion, this could result in cheaper, faster and better data services for the company, and a more rewarding career path for those who are passionate about data.

Late 2008 and throughout 2009 the gas prices started to fall, more so in the USA than in other parts of the world. Shale Natural Gas has caught up with the demand and was exceeding it.  In April 2010, we woke up to witness one of the largest offshore oil spill disasters in history. A BP well, Macondo, exploded and was gushing oil.

For companies that put all their bets on gas fields or offshore fields, they did not have appetite for data management projects. For those well diversified or more focused on onshore liquids, data management projects were either full speed or business as usual.

 2010 to 2015 ….

Companies that had enjoyed the high oil prices since the 2007 started investing heavily in “digital” oilfields.  More than 20 years had passed since the majors started this initiative (I was on this type of project with Schlumberger for one of the majors back in 1998). But now it is more justifiable than ever. Technology prices have come down, systems capacities are up, network reliability is strong, wireless-connections are reasonably steady and more. All have come together like a prefect storm to resurrect the “smart” field initiatives like-never before. Even the small independents were now investing in this initiative. High oil prices were justifying the price tag (multiple millions of dollars) on these projects. A good part of these projects is in managing and integrating real time data steams and intelligent calculations.

Two more trends appeared in the first half of the 2010s:

  • Professionalizing the petroleum data management. Seemed like a natural progression now data management departments are in every company. The PPDM organization has a competency model that is worth looking into. Some of the majors have their own models that are tied to their HR structure. The goal is to reward a DM professional’s contribution to business’ assets. (Also please see my blog on MSc in Petroleum DM)
  • Larger companies are starting to experiment and harness the power of Big Data, and the integration of structured with unstructured data. Meta data and managing unstructured has become more important than ever.

Both trends have tremendous contributions that are yet to be fully harnessed.  The Big Data trend in particular is nudging data managers to start thinking of more sophisticated “analysis” than they did before .  Albeit one could argue that Technical Assistants that helped engineers with some analysis, were also nudging towards data analytics initiatives.

In December 2015, the oil price collapses more than 60% from its peak

But to my friends’ disappointment, standards are still being defined. Well hierarchy, while is seems simple to the business folks, getting it all automated and running smoothly across all types and locations of assets  will require the intervention of the UN.  With the data quality commotion some data management departments are a bit detached from the operations reality and take too long to deliver.

This concludes my series on the history of Petroleum Data Management. Please add your thoughts would love to hear your views.

For Data Nerds

  1. Data ownership has now come full circle, from the business to IT and back to business.
  2. The rise of Shale and Coal-bed Methane properties, fast evolution of field technologies are introducing new data needs. Data management systems and services need to stay nimble and agile. The old ways of taking years to come up with a usable system is too slow.
  3. Data cleaning projects are costly, especially when cleaning legacy data, so prioritizing and having a complete strategy that aligns with the business’ goals are key to success. Starting with well-header data is a very good start, aligning with what operations really need will require paying attention to many other data types, including mealtime measurements.
  4. When instituting governance programs, having a sustainable, agile and robust quality program is more important than temporarily patching problems based on a specific system.
  5. Tying data rules to business processes while starting from the wellspring of the data is prudent to sustainable solutions.
  6. Consider outsourcing all your legacy data cleanups if it takes resources away from supporting day to day business needs. Legacy data cleaning outsources to specialized companies will always be faster, cheaper and more accurate.
  7. Consider leveraging standardized data rules from organizations like PPDM instead of building them from scratch. Consider adding to the PPDM rules database as you define new ones. When rules are standardized data, sharing exchanging data becomes easier and cost effective.  

Bring It On Sooner & Keep It Lifting Longer. Solutions To Consider For ESPs (Or Any Field Equipment)

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Settled on average 6,000 feet below the surface, electrical submersible pumps (a.k.a ESPs) provide artificial lift for liquid hydrocarbons for more than 130,000 wells worldwide.
Installing the correct ESP system for the well, installing it precisely, and careful monitoring of the system is paramount to reducing the risk of a premature end to an ESP life cycle. But the increasingly long laterals of horizontal wells, along with rapid drilling in remote areas, is creating challenges for efficient operations and the ESP’s life span. Implementing the correct processes and data strategies will, undoubtedly, be the cheapest and fastest way to overcome some of the challenges.

1- Implement A Process Flow That Works, Break The Barriers

When a decision is made to install an ESP in a well, a series of actions are triggered: preparing specifications, arranging for power, ordering equipment, scheduling operations, testing, and finally installing it in a well, to state a few. These actions and decisions involve individuals from multiple departments within an organization as well as external vendors and contractors. These series of actions form a process flow that is sometimes inefficient and is drawn out, causing delays in producing revenue. In addition, sometimes processes fall short causing premature pump failures that interrupt production and raise operational costs.
Research of many industry processes shows communication challenges are one of the root causes for delays, according to LMA Consulting Group Inc. Furthermore, communication challenges increase exponentially when actions change hands and departments. A good workflow will cut across departmental barriers to focus on the ultimate goal of making sure Engineering, Procurement, Logistics, accounting, vendors, contractors and field operations all are on the same page and have a simple and direct means to communicate effectively. But more importantly, the workflow will allow for the team to share the same level of urgency and keep stakeholders well informed with the correct information about their projects. If you are still relying on phones, papers and emails to communicate, look for workflow technology that will bring all parties on one page.

A well-thought through workflow coupled with fit-for-purpose technology and data is critical, not only to ensure consistent successful results each time but also to minimize delays in revenue.

2- ESP Rented Or Purchased, It Does Not Matter… QA/QC Should Be Part Of Your Process

Although ESPs are rented and the vendor will switch out non-performing ones, ensuring that the right ESP is being installed for a well should be an important step of the operator’s process and procedures. Skipping this step means operators will incur the cost of shut downs and tempering of reservoir conditions that may otherwise be stabilized – not to mention exposure to risks each time a well is penetrated.
More importantly a thoughtful workflow ensures a safe and optimal life span for ESPs regardless of the engineers or vendors involved, especially in this age of a mass retiring of knowledge.

At today’s oil prices, interrupted production for a well of 1,000 barrels per day will cost an operator at least $250,000 of delayed revenue for a 5 day operation. Predictive and prescriptive analytics in addition to efficient processes can keep the interruption to the minimum if not delay it altogether.

3- Know Why And How It Failed Then Improve Your Processes – You Need The Data And The Knowledge

One last point in this blog: Because ESPs consist of several components, a motor, a pump, a cable, elastomer, etc… ESP failure can, therefore, be electrical, mechanical, thermal or fluid/gas composition. Capturing and understanding the reasons for a failure in a system to allow for effective data analysis provides insight that can be carried forward to future wells and to monitoring systems. Integrating this knowledge into systems such as predictive analysis or even prescriptive analytic to guide new engineers will have an effect on operator’s bottom-line. A few vendors in the market offer these kind of technology, weaving the right technology, data and processes to work in synergy is where the future is.

On how to implement these solutions please contact our team at info@certisinc.com.

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Cut Search Time for Critical Documents from Days to Seconds. It is Time to Stop Digging in Folder Structures

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It wasn’t long ago when geoscientists and petroleum engineers at one renowned oil company might spend days searching for documents.  “Searching” meant digging through folders (as many as 1500 of them!!), and discerning whether a “found” file was an official report or only an earlier draft.  To give you an idea, some critical HSE documents were buried as deeply as within the 13th   sub-folder (and then the correct version had to be selected!!)

Obviously in this situation emergency and critical decision cycle times were lengthened by the difficulty of finding the “buried” technical documents. The average time to locate and validate the accuracy of a document was calculated at 3 days.

When Certis arrived, the company’s folder system looked like an episode of “Hoarders”. The hoarder believes there is an organized system to his “madness”, but nobody else in the home can quite figure it out. Over the years, over 2,000,000 documents had been amassed at this location, and that total was growing fast. As engineers and geoscientists floated in and out, the system fell victim to hundreds of interpretations. Unlike the hoarder’s goods, these documents contained vital information that accumulated years of studies and billions of dollars of data acquisitions. Years of knowledge, buried, literally.

In today’s competitive and fast pace operations in our Oil and Gas industry, data is accumulating faster than ever and decisions must be made faster than ever by petro-professionals that are already overextended.  Compounded with the fact that a large portion of the knowledge is within a workforce that may soon retire means that Oil and Gas companies that want to stay exceptional and competitive cannot afford to waste petro-professionals time hunting for critical records.

So, how do you get to a point where your organization can locate the right document instantly?  We believe it is all about Processes, Technology and People put in place (a cliché but so true)

When Certis completed this project, the technical community could locate their documents within few seconds using “google-like” search. More importantly they were (and are now) able to locate the “latest” version and trust it. The solution had to address 3 elements, people, processes and technology.

The final solution meant collapsing folders from 2000 down to 150, using a DRM system without burdening the technical community and implementing complete processes with a service element that ensured sustainability.

Centralized, standardized and institutionalized systems and processes were configured to take full advantage of the taxonomy and DRM systems. Once the ease of use and the value were demonstrated to the people, buy-in was easy to get.

Technology advances faster than our ability to keep up. This is especially true when working with professionals whose focus is (and should be!) on their projects, not on data management. We had to break the fear of change by proving there is a better way to work that increases efficiency and makes employee’s lives easier.

Legacy Documents, what do you do with them?

Because solving operational issues at the field requires access to complete historical information, exhuming technical legacy documents, physical or electronic, from their buried locations was the next task.

On this project the work involved prioritizing, locating, removing duplicates, clustering, and tagging files with standard meta-data. With a huge number of files accumulated in network drives and library rooms, a company must keep an eye on “cost/ benefit” ratio. How to prioritize and how to tag technical files become two key success factors to designing a cost-effective migration project.

This topic can go on and on since there were so many details that made this project successful. But that may be for another post.

Read more about Certis and about our oil and gas DRM services http://ow.ly/oRQ5f