The Importance of Production Data Across the Organization02/20/2019
Almost every discipline, department, and system in an upstream oil and gas company relies, to some extent, on access to current and historical production data. This makes it one of the most valuable resources and requires that it be validated, reliable, and consumable in the formats that each user requires.
Production data can mean different things to different people across the organization, depending on their disciplines.
For instance, in the field, production data traditionally refers to all aspects of raw measurements captured manually by field operators and technicians, surveyed by SCADA systems, or used as key performance indicators (KPIs) to monitor well and equipment performance against targeted operating parameters. Examples of these include pressures, temperatures, odometer meter readings, sales volumes, run ticket values, compressor run times, well test readings, and multiple other measurements.
Speaking of well tests, they are often referred to as a well’s “theoretical production” for the period the test is valid because they represent the oil, gas, and water that a well is theoretically capable of producing over a 24-hour period, given certain standard conditions. That being said, unless there is continuously measured multi-phase separation, this is not the actual production of the well.
In the production accounting world, production is an all-encompassing term for the multiple streams of measured volumes that are attributable to wells with shared measurements within a hydrocarbon allocation network. For example, a set of three wells (A, B, and C) may flow to a common gas sales point. Well A also has gas that is flared, and wells B and C require compression to reach the sales point. In this case, based on the appropriate allocation methodology:
- Well A’s production would be the sum of its portion of sales, plus flare.
- Well B’s and C’s production would each be their portion of the sales and gas used by the compressor.
In the world of production engineering and asset management, the focus will not only be on how much oil and gas a well produced or sold as a whole, but also how much can be attributed to the operator’s ownership percentage in the well. The former is referred to as Gross Production, the latter as Net Production.
The above are a few simple examples of how the term production is different based on the type of data and the consumer of the data. It’s not uncommon for there to be upwards of 50 individual disciplines that consume some form of production data. The constant availability of that data at the right time in the right place in the right person’s hands is the lifeblood of an oil and gas company. Ask anyone whose role it is to administer production reporting systems what their day looks like if one of their systems is missing data or has stopped working for some reason. It’s visible across the organization.
The Different Uses of This Data Within Different Departments
- Field Operators capture production data such as pressures and tests volumes. This data can help each field operator prioritize which wells they should focus on each day based on known issues and maintenance.
- Operations include the field, foremen, and superintendents who are responsible for gathering raw production data and ensuring its accuracy. This data is then trended and analyzed to make smarter, faster decisions and accurately maintain and optimize production for any given well and asset.
- Engineers use production data to make decisions on forecasts and budgets, focusing on cost effectiveness. They also work with geologists on what wells they want to drill – plotting on future wells based on the performance of existing wells, which relies on accurate production data.
- Joint interest billing uses production data to determine what to charge interest owners for lease use.
- Productions accounting is responsible for daily and monthly reporting, regulatory reporting, and ensuring the accuracy of data sent to revenue – all of which is based on production data.
- The Revenue department pays interest and royalties, balances books and accruals, and is responsible for accruing at the end of every month. If the revenue department doesn’t receive good daily production data, they’re only estimating what they’ll get paid each month. Accruals need to be very accurate to match what they’re getting paid and can be tied back to good, accountable data capture.
- The Marketing team uses the production data to hedge or price the product. As they work with the purchasers, they need to know what the wells are producing, how much there is to sell, and where from.
- The Land team uses the production data to help determine new wells, division of interest (DOI), and well status. They need to be able to understand from the production data how much of the production the company owns. If the well is “held by production,” land needs to know as soon as possible if the well isn’t producing for any length of time.
- Asset Managers use production data to understand asset status, production volumes, and key performance indicators – how the wells are doing compared to others.
- Executives rely on production data to understand overall company key performance indicators. How is the company’s new well doing? Which is our best division?
Best Practices for Gathering, Managing, Integrating, & Reporting Multiple Forms of Production Data
Start with a defined set of processes for the capture and validation of raw production data – whether real-time, daily, periodic, or monthly. Acceptable variations from expected values must be defined, including the frequency of capture, who is responsible for validation, and the right actions to address discrepancies. Using one tool for those tasked with gathering data in the field helps minimize the effort and supports a focus on the prescribed processes. Data doesn’t necessarily need to reside in one place. It’s more important to use a tool that can aggregate and distribute data to and from multiple sources, minimizing time spent in the field moving in and out of systems – while providing a wholistic view into the validity and quality of the data that is being captured for each asset.
For example, while capturing all the standard pressures, downtime, gauges, and well tests for a specific set of wells and equipment on a pad, there may be an overdue inspection on the same pad. Part of that data will flow to a production data management system and the other to a maintenance system, but they’re all part of the greater “production data” ecosystem.
When it comes to data flowing to other systems, seamless and tight integration is key. The disparate nature of the disciplines consuming production data means that the same data will have to move across multiple systems. Revenue, forecasting, and regulatory reporting systems all require well-level production (gas vs. oil, sales vs. production, etc.) volumes to run, perform, and complete their tasks. In this case, it’s critical that the source of that production data – the production data management system where the hydrocarbon allocations occur – provides one version of the truth. Recalculating production in different systems will lead to discrepancies and errant decisions based on different versions of the truth.
When it comes to reporting tools, arguments can be made for a single corporate-wide reporting system for all data across all departments and disciplines. The reality is that based on the type of data, the overhead of maintaining each tool, and who is consuming the data, purpose-specific tools sometimes can make sense. The key is to, where possible, not move data from system to system or data source to data source when it’s being used for reporting. Instead, one should leave the data that is being reported within the source system it resides but have the ability to view all data in one place.
And of course, all the requisite features that should be included: tabular and graphical views, the ability to configure focused dashboards, aggregation of data across multiple levels of hierarchies, multiple types of hierarchies, self-serve configuration, configurable calculations based on published data streams, sharing of data, and the ability to export data to a spreadsheet program for additional manipulation. For scenarios where pixel-perfect, printable reports are required, the ability to schedule and distribute reports on an ad-hoc and scheduled basis is important.
Three Examples of Different Reporting- & Analytics-Focused Applications
- For corporate-wide production volumetric data, the reporting system should be simple and require minimal training. One key feature included should be drill-down capabilities to more granular production data with specific data about individual assets and wells. This is helpful so that you don’t have to jump out of one system into another to mine additional details.
- Another reporting solution focuses on bringing data together across multiple disciplines. For example, enable key streams from revenue, production, and land to see production data in the context of other leading indicators, like ownership, lease operating expenses, and revenue.
- A more specific and focused example of data reporting and analytics would be a route surveillance dashboard targeting field operations and engineering. It may include real-time SCADA combined with historical metrics for each asset, plus monitors and alerts with a view into which route these assets are on and who is responsible for that asset today.
When it comes to integrating and reporting on production data in an upstream oil and gas organization, the first order of business is to understand how each consumer or discipline uses the data and when. Do they need it to run calculations in another system? Are they looking for KPIs? Do they need it weekly, daily, or multiple times a day? Another important thing to understand is how granular the data needs to be. Should it be rolled up to a corporate level, a division level, or perhaps the well or equipment level?
To ensure that quality production data is flowing throughout an organization’s system and is being reported, it’s also important to understand all sources of data – as there could be opportunities to reduce duplicate data streams and streamline processes. Finally, it’s important to continually elicit input and feedback from the consumers of production data to determine whether their needs have changed, so that the data remains reliable across the organization.
About The Author
Clara Fuge is a Vice President of Product Management at P2. With more than 20 years’ experience providing software solutions to the energy industry, her expertise lies in upstream hydrocarbon accounting and production operations. Clara graduated with a degree in Economics from the University of Texas at Austin and is a member of several industry groups, including the American Petroleum Institute’s Committee on Production Measurement & Allocation. A self-proclaimed “allocations geek,” she is passionate about giving oil and gas companies the tools needed to report accurate well production. When she’s not working, Clara enjoys spending time with her husband and their three dogs.