Investing in the energy space is a risky endeavor. Wells cost millions to drill and often take up to several years to break even, if they make money at all. With oil prices at historic lows, how can investors minimize risk and make better, more confident decisions?
When an analyst at an investment firm was tasked with evaluating potential opportunities in the Eagle Ford, she honed in on two counties with available prospects. She wanted to know which of these two counties offered the most promising acreage at $50 oil.
Using Drillinginfo and the Well Production Economics workflow, the analyst computed financial metrics for a typical well in each county. She created cash flow models based on specific oil prices and well costs, and sensitivity charts that tracked how ROI would vary as oil prices and well costs changed. Based on the results of this workflow, the firm identified a potential well that was predicted to break even at just under $40 oil for further due diligence.
To calculate potential ROI, the analyst must estimate future production from each potential well. She does this by analyzing historical production in each county of interest and creating decline curves.
Using the proprietary Graded Acreage module in DI Analytics, the analyst selects only wells from each county that were drilled in acreage that is of similar quality to the firm’s potential wells. Using the data from these wells, she can create a type curve in seconds that will estimate production for a well drilled in similar quality acreage in each county. The ability to select data from only relevant wells allows for a more accurate prediction.
Without Graded Acreage or DI Analytics, the analyst would have to manually collect historical production data from wells in each county of interest. Other economic software have no way of sorting wells by acreage quality, so the analyst would have to include data from wells of varying quality, resulting in a much less accurate type curve.
Estimate Expected ROI
Besides level of production, there are multiple economic inputs that impact the expected ROI on a well. The analyst needs to build a model that will predict returns based on specific economic conditions in each county.
Using pre-loaded analytics-grade data included in DI Analytics and available through the Well Production Economics workflow, the analyst builds a cash flow model based on $50 oil, a well cost of $7M, a discount rate of 10%, and tax rates and royalty burdens specific to each county and opportunity. With a simple click, the analyst generates before- and after-tax IRR and payout period for each potential well.
Because no other software is pre-loaded with well data, the analyst would have to manually collect relevant data and build a model that incorporates economic inputs and predicted production. This is a time-consuming and tedious process.
Calculate Impact of Changing Variables
When oil prices are low, there are far fewer areas where it is economic to drill. Wells that generated 50% ROI at $70 oil might not be profitable at all at $50 oil. The analyst needs to understand how ROI on the firm’s prospective opportunities will be impacted by changing variables.
With the Sensitivity Analysis feature in DI Analytics, the analyst charts the degree to which each potential well would be impacted by changing oil price, well cost, and discount rate. Within seconds, she can see how the payout period and ROI of each well would change as oil prices rise or fall, well cost is increased or decreased, and the discount rate changes. With this data, the analyst can easily understand which well is likely to be more greatly influenced by changing variables.
Without the simple Well Production Economics workflow, the analyst would need to export her existing production and cash flow data into Microsoft Excel and plot sensitivities. This takes valuable time that could lead to lost opportunities.
In less than an hour, the analyst was able to complete an analysis that used to take days. The Well Production Economics workflow in DI Analytics allowed the analyst to select pre-loaded, analytics-grade data to work with and, in the same application, create custom decline curves and economic inputs for multiple scenarios.
With the workflow’s side-by-side analysis capabilities, the analyst could visualize which potential well was predicted to generate higher returns. She could also chart how the returns would vary if oil prices were to rise or fall or if the cost of drilling and completing the well changed.
The investment firm was ecstatic with the results. Finding a profitable opportunity in a low-price environment can be a difficult task. With Drillinginfo, the firm identified a promising prospect within minutes and beat their competition to a valuable investment.
Drillinginfo is redefining the oil and gas investment process. Contact our team to learn more about how you can beat your competition to the best opportunities, regardless of oil price.