5 reasons your e&p company needs master data management · the formats of well and lease names...
TRANSCRIPT
D A N I E L P E R N A
MANAGER, OIL & GAS CONSULTING, EPAM
5 Reasons Your E&P Company Needs
Master Data Management
W H I T E P A P E R
J A N U A R Y 2 0 2 0
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INTRODUCTION ...................................................................................................................................... 3
INCOMPLETE APPROACHES TO DATA MANAGEMENT ....................................................................... 4
MAKING THE CASE FOR MASTER DATA MANAGEMENT ..................................................................... 6
MASTER DATA MANAGEMENT AND THE FUTURE OF YOUR COMPANY ......................................... 11
Table of Contents
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Introduction
Imagine that the Chief Operating Officer (COO) of your E&P company needs to provide investors with information quickly. He asks his finance, geoscience, engineering, and land people to give him a list of wells in which the company has financial interest, that have this specific producing formation, and that are not abandoned, and then to plot them on a map. They tell him there’s no one place in the company that has the answer, so they return with several separate lists.
The COO assigns a data analyst to work through these lists and to create the map he wants. Overwhelmed, the analyst finds that none of the lists match completely. She requests a team that spends weeks matching up the wells from each source, checking source documents for accurate values, analyzing the meaning of each status, and standardizing status and formation names. At the end of their analysis, the analyst and COO conclude that each discipline’s list was partially right and that all of this work was, in fact, necessary to get an accurate answer.
If this scenario sounds familiar, you’re not alone. Inconsistent well data across siloed systems is a common and costly problem for exploration and production (E&P) companies that severely hinders strategic initiatives. To be clear, this is not just a problem for executives—this is a problem for everyone who needs to make decisions or interpretations from data across multiple teams or disciplines. Recent surveys reveal that data scientists1 and E&P professionals2 spend 40-80% of their time finding, cleaning and organizing data before they can effectively use it.3
1 https://visit . f igure-eight .com/rs/416-ZBE-142/ images/CrowdFlower_DataScienceReport_2016.pdf
2 https://www.onepetro.org / journal-paper/SPE-0909-0048-JPT
3 https://www.kaggle.com/sudhirnl7/data-science-sur vey-2018/notebook
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Incomplete Approaches To Data Management
Where to store your data: Repositories like data lakes,
data warehouses, and the cloud give you one convenient place
to analyze data from many sources
How to move your data: Automated middleware like message queues, ETL tools,
enterprise service buses, and event stream processors
transmit your data from point A to point B in the desired
transformed format
How to analyze your data: Tools like dashboards, artificial intelligence (AI), and machine
learning provide insight into your data and generate
predictions that you otherwise would not have seen
So, what is a realistic way to solve this problem? Let’s start with what it’s not. There are a lot of powerful and exciting technologies today pertaining to:
As truly valuable as these tools are, they still don’t solve many of the problems illustrated above. That’s because they’re still not designed to do the foundational work of mastering critical data across disciplines in your enterprise. However, there is a viable solution. Master Data Management (MDM) is a wholistic methodology that uses specialized MDM software to accomplish all of the following:
• Define, standardize, and govern data objects, attributes, names, computations, and hierarchies
• Match up data objects from multiple sources that are important across your E&P business
• Blend different data versions based on detailed logic
• Include context about the sources of the data being used
• Produce a single ‘gold’ record for each entity in a single central system that represents the most trusted source of the truth for the enterprise
• Share the gold record with all disciplines, systems, and platforms that need it
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Incomplete Approaches To Data Management (cont.)
MDM is different than simply moving data to a single place. MDM systematically addresses the messy nuances in what exactly the data represents according to each source, how different disciplines use it, and what the best approach is for the enterprise to manage each entity. Because of this, it provides the critical foundation for having clean, consistent, accessible data across your company where and when you need it.
Ad hoc solutions, silos, redundant data entry, and point-to-point integrations
Master Data Management “hub and spokes”
VS
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Making The Case For Master Data Management
YOUR ANALYSTS, DATA SCIENTISTS, AND INTERPRETERS ARE TRYING TO MASTER DATA LOCALLY BEFORE THEY CAN DO THEIR JOBS
The term ‘mastering’ may not commonly be used at your company, but most of your decision-makers and analysts regularly do it to some degree without realizing. Your people understand that an interpretation is only as trustworthy as the data fed into it. So, whenever an interpreter, data scientist, or technologist takes data from multiple sources and tries to establish a blended version with the most reliable data while using a set of consistent values, they’re doing a form of mastering. For example, they may prefer a well surface location validated by GPS over one from a data vendor, or their queries may be undermined by 37 variations of one operator name, so they change them all to a single standard.
Some people master data routinely and manually in spreadsheets. Some follow painstaking workflows where they iteratively load and then lock certain attributes before loading more, while others give similar requirements to software developers who do a form of data mastering from different sources in their code as they move it.
By doing this, people all around your organization are demonstrating that they need mastered data. They have the right idea about how data must be used to reduce risk and increase the value of their interpretations, but they are stuck with methods that are repetitive, inconsistent, and/or manual.
What if there were a detailed, automated, and consistent way to master data for your whole organization?
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More and more E&P companies are being awakened to the benefits of Master Data Management as a cure for inefficiencies that burn time, energy, and money across their organizations. To illuminate these benefits, here are five reasons your E&P company needs MDM:
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Making The Case For Master Data Management (cont.)
YOUR E&P DISCIPLINES ARE UNAWARE OF BETTER DATA
To maximize the value of data, it must be freed from its organizational silo. Let’s say a subsurface team wants to minimize costs and maximize production by making their subsurface interpretation as accurate as possible and by ensuring that they land each well in the right target formation. Their technologists research and correct well elevations in their interpretation project for an entire county of wells.
How many people benefit from this data clean-up? Only a dozen or so perhaps—just the people who use that project and to whom that team has spoken directly. Other analytics teams, GIS teams, and E&P teams with overlapping areas of interest don’t even know that this cleaned-up data exists. So, each of these teams must either redo research that has already been done, spend time asking if anyone has done it, or simply use sub-par data.
Elevation is just one example. Consider just a few costly risks that skyrocket when people cannot access data at the right time, such as well location, well trajectory, well logs, or leases and permits:
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FAILING TO EXECUTE LEASES OR PERMITS ON PRODUCTIVE AREAS
AS QUICKLY AS A COMPETITOR
ALLOWING A VALUABLE PERMIT OR LEASE TO EXPIRE
FAILING TO PREVENT AN AVOID-ABLE HOLE COLLAPSE OR SIDE-
TRACK
DRILLING A WELL IN THE WRONG PLACE
COLLIDING WITH ANOTHER WELLBORE WHILE DRILLING
FAILING TO PREVENT AN AVOIDABLE WELL BLOWOUT
FAILING TO ACCURATELY ASSESS A GROUP OF WELLS OR ACREAGE
BEFORE ACQUIRING THEM
DRILLING A WELL WHOSE PERMIT WASN’T APPROVED
FAILING TO FULFILL ENVIRONMENTAL
RESPONSIBILITIES ON A WELL
RUNNING A NEW DEVIATION SURVEY BECAUSE YOU CANNOT
FIND THE EXISTING ONE
Your company can lose millions—sometimes billions—in lawsuits, regulatory fines, lost production, lost opportunity, wasted time, and lost investment.
Wouldn’t it be nice to know that if someone loads or fixes critical data in one system, other disciplines around the company can easily find and use it?
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Making The Case For Master Data Management (cont.)
YOUR E&P DISCIPLINES DON’T AGREE ON IMPORTANT TERMS AND DEFINITIONS
Agreeing on definitions of terms—both conceptual and technical—allows for clear communication. Imagine that you run a school where no one can agree on the difference between a parent and a child, so your staff mixes up data about them. That may seem absurd, but this is often true for wells.
Wells are conceptually made up of parent and child components. Multiple completions can belong to one parent wellbore and multiple wellbores can originate from one parent surface location. Some say that deepening a well creates a new parent (wellbore) for completion data. Others say that this event is a new child (completion) on an existing parent (wellbore). Similarly, let’s say you spud a well and must abandon it after drilling only a few hundred feet. When you restart drilling at a new surface location forty feet away, it is common for disciplines to disagree on whether this should be tracked as a different wellbore on the same well or a brand new well. If data users and interpreters are not using nuanced definitions, it will decrease data quality and result in costly problems.
In addition to concepts, attributes also need to be defined. What’s the definition of well status? Your accounting department might consider ‘sold’ as the final well status for accounting purposes, but E&P teams continue to care if that well status is ‘producing,’ ‘shut-in,’ or ‘abandoned’ for operational purposes, regardless of whether it was sold. Employees who should be focused on interpreting the data instead spend thousands of hours per year reviewing, cleaning, and/or transforming data due to overlapping, confusing, or inconsistent data definitions.
What if there were a way to manage data with consistent definitions in one place for the whole enterprise?
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Making The Case For Master Data Management (cont.)
YOUR E&P DISCIPLINES CAN’T MATCH WELL RECORDS BETWEEN SYSTEMS
Consistent and complete identifiers help us find the same thing in different environments. If your child-hood best friend later changed her name, it will be harder to find her now. Conversely, your childhood best friend and your niece may have identical names, but that doesn’t make them the same person. In the same way, well names and numeric identifiers in the industry are not always sufficient for matching. The formats of well and lease names can differ, characters may be added and removed, words may be rearranged, different wells may have the same name, and the names can legally change over time. In some parts of the world, legal unique well identifiers are created by the operator or vendor and are not governed by a regulatory standard.
Even when there is a standard and more regulator y consistency, certain challenges remain. The API number in the US, for example, has practical problems with consistency because various regulator y agencies, data vendors, and operators use different methods to identify the same well components. Furthermore, the arbitrar y identifiers assigned by software packages are also unreliable for matching because each software is different. All of this is exacerbated in proposed wells, when the identity of the well is still in flux.
It takes complex logic, in addition to those identifiers, to reliably match well identities. Employees who should be interpreting the data instead spend thousands of hours per year trying to match well records due to inconsistent well identities and identifiers.
What if your company had a single system and team that solved this complex problem in one place for your company and maintained a cross-reference of well identity across all key sources?
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Making The Case For Master Data Management (cont.)
YOUR E&P DISCIPLINES DON’T TRUST DATA
It requires trust to consume something that will affect us. Imagine that you receive an unlabeled package of food in the mail. The food looks good, but can you trust it? You may wonder: Who made it? When was it made? Should it be refrigerated? What ingredients are in it? Who is it really intended for?
Wouldn’t it be nice if there were a label on the food answering those questions so that you could be confident in whether consuming it would benefit you or harm you? Data is no different. The location of “well X” might have been manually verified three times before someone loaded it in the current system, but how would the interpreter know that? They’ll have to take time away from their regular work to verify it before trusting it. Employees who should be interpreting the data instead spend thousands of hours verifying or re-verifying data due to unknown data vintage.
What if there were a central way to capture different versions and expose the “metadata” labels—the data about the data—for important attributes so each interpreter knows who entered it, when, from which source, why, and how? Good news: there is!
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Master Data Management and the Future of Your Company
Master Data Management means trusted data—consolidated, blended, accessible, governed, and traceable data across your enterprise . On top of that, by its interconnected nature, it cultivates a common understanding, fewer silos, more accountability, better processes, better data quality, and better analytics—all of which should reduce your costs and increase your revenue. That may be why, according to a 2018 Global Data Management report by Experian, 38% of companies sur veyed across industries have planned an MDM program; twice as many as in 2017.4
Finally, an effort like MDM can be compared to physical fitness. In the same way that it takes more than simply buying a treadmill to keep you physically healthy, it takes more than buying a piece of software to keep your data healthy. MDM is a wholistic and ongoing effort driven by an attitude that values data-driven decisions, that aspires to have a cohesive organization, and that recognizes that we are in a digital age. It requires a new and better approach that involves people, processes, and technology. And just like a healthy lifestyle leads to a better mood, less stress, more energy, and longer life, a good Master Data Management foundation can ensure your company lives a long, healthy, prosperous life in this digital age.
http://www.experian.com/blogs/insights/2018/02/2018-global-data-management-benchmark-report/
4 http://www.experian.com/blogs/ insights/2018/02/2018-global-data-management-benchmark-report /
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