Generating a production or capital forecast is comprised of more than just decline parameters and activity costs. A true forecast is representative of the inclusion of an entire network of data inputs and assumptions, all interdependent on one another. And let’s face it, those assumptions can change more frequently than once a quarter.
CONSOL Energy’s strategy of organic growth focuses on rapidly developing its natural gas and coal resources. Achieving that strategy hinges on understanding the exact potential and risks of all of its assets at any moment, and over time.
The CONSOL Planning team decided to ask the question, “Is there a way to see a holistic corporate forecast across all assets in our company, taking into account every aspect of the business from a wellhead to a sales point?”
In 2014, CONSOL adopted enersight as their asset development solution. In what follows, I will discuss how we consolidated their production and capital data from a corporate perspective, and incorporated input from all business functions to arrive at a cohesive and realistic forecast.
Single Asset Modelling
In some companies, one department will apply enersight planning to model one asset and its network of production and scheduling parameters. For example, a reservoir engineer uses enersight to model production and capital forecasts with what-if scenarios based on variables like type curve parameter changes or risk factors. Those forecasts are plugged into various spreadsheet models downstream of the reservoir engineer, that data is massaged in each sheet (be it shrink, top-level risking or downtime applied), and eventually reports are issued and decisions are made using this data. Ultimately, the reservoir engineers are responsible for the forecasted production values, but what happens in the intermediate steps between what enersight outputs and a finalized forecast? How does a company ensure that the same assumptions are applied for every forecast, quarter by quarter or even asset by asset?
Integrated Asset Planning
CONSOL Energy took the approach that enersight’s model would be the means to centralize data and standardize assumptions that every business function uses into one location. What they saw was that not only does this impose a consistent “baseline” for which all outputs can refer back to, but it highlights potential risk due to various industry factors and improves visibility across the company as a whole.
This visibility is what CONSOL Energy is seeking to ascertain the condition of the company and determine what decisions to make in order to maximize profit for shareholders. As Chris Miller, VP of Strategic Planning at CONSOL Energy, put it, “We do not want to spend our time putting out fires and reacting to unforeseen circumstances. We want to be able to make deliberate and carefully measured decisions, but I always say that you have to be able to measure it before you can manage it”.
CONSOL Approach Examined
To achieve visibility and reliability in forecasting, CONSOL focused on four principles
1. Centralize and Standardize
CONSOL took the approach that while it is the Planning team’s job to generate integrated forecasts, risks and what-if scenarios, those integrated forecasts should be comprised using the same data and method by every business team contributing their own department’s portion of a forecast. If a production forecast is generated from the Reserves team using a certain lateral length, that same lateral length should be used in a production forecast issued from Planning. If Marketing is forecasting capacity volumes based on certain shrinkage or extraction values, those values need to match the values Planning is using. By forcing all of these data points into each enersight model, CONSOL is able to ensure that all forecasts and planning guidance out of enersight is calculated using the same, standardized baseline assumptions. The standardized planning model has both enforced data accuracy and completeness; and consistent assumptions about risk and opportunity the company can stand behind.
Figure 1: Data Centralization Using enersight
2. Proactivity, Not Re-activity
In an actual field, every change to a plan or infrastructure initiates another change in the network. For example:
If a gathering facility has a fire and is shut down for an extended amount of time, how does that affect production of inflowing wells; and, how do you reflect that in the next forecast?
Is building a pipeline to an extraction facility a viable solution?
If I defer activity on this pad until next month or if I move this rig, what is the economic impact; furthermore, what is the impact on a facility with a constraint?
These are all questions that, when posed, are hard to generate an answer to without utilizing a model that demonstrates the interdependency of all aspects of the field. CONSOL saw that an increase or decrease in maximum capacity at a gathering facility could not only be forecasted ahead of time to mitigate exposure to changes, but the impact at every decision point upstream of that facility could also be tracked all the way to the sales point, and adjustments could be made accordingly. Their goal in utilizing enersight was to get a true-to-life model of the characteristics of a field, and be able to generate what-if scenarios for potential events or changes, thus creating the ability to be proactive in their decision-making. In order to do so, they had to get not only the Planning team involved, but the Marketing team too. Having all data maintained and up to date allows CONSOL to generate a true reflection of how one aspect of the field is dependent upon another. They are able to leverage this continuous and thorough understanding of their operations to generate more accurate projections, foresee decision points, and ultimately manage their business more effectively.
3. “In Order to Measure it, You Have to Manage It.”
Not only does CONSOL want to be able to stay ahead of situational changes, the company wants to be able to identify, define and measure key indicators of the industry. Using enersight to divide activity on a well into customized steps with differing attributes, CONSOL was able to take generic lump-sum cycle time data and split it into measurable parts to start pinpointing if and where bottlenecks were occurring, or where capital was being misallocated. Using enersight to model facility constraints and pipeline priorities and schedules, they were also able to visualize the subsequent influence on deferred production resulting from direct application of these constraints. Modeling this level of detail, as opposed to high level adjustments, provides the ability to measure their sensitivity to individual controls. Once the company could visualize and measure these variables and their impact, they began to manage their assets accordingly, and gained the ability to take actions such as reducing cycle times and redistributing capital to improve returns on investment.
