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DUC, DUC, GOOSE: In a sub-$30 oil environment how can NBL maximize returns with less CAPEX spend in their Delaware asset?

March 25, 2020

About the author

John Chaplin

John Chaplin is a Technical Advisor at Novi where he applies his background in A&D evaluations to ensure Novi's predictive analytics and economics help customers develop better decisions in the field. Prior to Novi, John held various roles in A&D groups at SIPC, Merrill Lynch and Morgan Stanley.

Given the extreme capital constraints imposed by a lower commodity price environment, many operators have announced CAPEX reductions and significant rig layoffs. Given these reductions, it would make sense to apply what capital remains to complete through DUC (Drilled, but UnCompleted) wells. If this is true, it would also make sense to revisit the completion designs to see if there are designs that might offer better cashflow in the short term while doing minimal damage to long term results.

In This Post:

  • What is NBL’s Delaware Basin duc inventory and how much will it cost to develop?
    • What completion designs result in the best economics at a $20 flat oil price?
      • How much value is added through optimization of the development strategy?
        • Conclusions

          Using Novi’s machine learning platform we will dive into the strategies being currently deployed by NBL and determine if value can be gained using alternate completion designs with their existing DUC inventory.

          What is NBL’s Delaware Basin duc inventory and how much will it cost to develop?

          Noble has 55 current DUCs in the Delaware basin acreage (highlighted in green, pdp wells in black)

          From Enverus, we have pulled down the DUCs for Noble Energy in the Delaware basin. There are approximately 55 DUCs split between several units across their position. To complete this analysis, we are going to run these DUCs through Novi at 4 different completion designs to determine what is the best return at our lower commodity price.

          Two distinct historical fluid volumes for Wolfcamp and Bone Spring implemented by NBL of 2,500 lbs/ft and 800 lbs/ft respectively
          Two distinct historical fluid volumes for Wolfcamp and Bone Spring implemented by NBL of 2,000 gals/ft and 550 gals/ft respectively

          Historically, Noble has employed two distinct completion designs on their inventory:

          • Noble Wolfcamp: 2,500 lbs/ft of proppant and 2,000 gals/ft of fluid
          • Noble Bone Spring: 800 lbs/ft of proppant and 550 gals/ft of fluid

          The surrounding offset operators have mainly completed using the same 2,500 lbs/ft of proppant loading with varying fluid to proppant ratios of 1.0-1.2, which differs from Noble’s 0.8 ratio. We will add these two test cases as well to see if other operator designs can give us insights:

          • Other Operators 1.0 Fluid Ratio: 2,500 lbs/ft of proppant and 2,500 gals/ft of fluid
          • Other Operators 1.2 Fluid Ratio: 2,500 lbs/ft of proppant and 3,000 gals/ft of fluid
          Source: Noble’s March 2020 Investor Handout states a ~$7.8MM capital cost for a 7,500′ lateral well

          Making some base assumptions of split on D&C costs and tying to the stated disclosure from NBL’s latest investor materials above, we developed a cost model in Novi Forecast Engine based on:

          • 4 completion designs that scale cost per lateral foot in a manner similar to NBL’s stated costs in the above mentioned investor materials.
          • Reduced the variable completion cost in the 3rd Bone Spring design by ~33% since we cut proppant and fluid by that much on a relative basis.
          • Increased variable cost by $50/ft for the increase in 500 gals/ft in completion fluid in the two offset operator designs.

          Below is a table of these costs and their implied total cost for a 7,500′ lateral. If NBL were to complete all of these 55 DUCs at the historical Wolfcamp design this would total to ~$302MM in capital spend for the completions at the stated capital costs.


          What completion designs result in the best economics at a $20 flat oil price?

          After running NBL’s DUC inventory through Novi’s Forecast Engine platform at the 4 different completion designs from above we can begin to gain insight into what is driving the production of these future wells. If we jump right into the economics at a $20 flat oil price we can see that the inventory splits between the two distinct groups, those that are more economic with a Noble Wolfcamp design and those that are better at a 3rd Bone Spring design. At $20 oil though all locations are more economic at the lower Bone Spring design.

          There is a clear delineation of the most optimal design for each well, with only a few supporting the use of a larger Wolfcamp design

          We can also see that the completion design chosen depends on the price deck, in the image below we can see that at the lower price decks the smaller Bone Spring design begins to become the more economic design but at a $50 price deck the best design is actually the Wolfcamp A for some of the wells. Also the other operator designs do not seem to be getting an uplift from the increase in fluids and do not support the additional cost.

          As oil prices increase the larger designs begin to become more economic but only for a subset of the wells

          If we optimize for NPV at $50 oil we get 16 of the wells being recommended by Novi for the “Wolfcamp Design” and the other 39 Novi recommends the “Bone Spring Design”. When we look into the reasons for the split between these two, we begin to see Novi’s machine learning model begin to take into account the several different well spacing designs of the DUCs. The model predominately picks wells with closest lateral neighbors of 1,500+ feet for the larger Wolfcamp design. The wells that are more tightly spaced with neighboring wells within <1,000 feet see much more degradation with the larger designs.

          The wells that are within 1,000′ of another lateral prefer the smaller design while the wells that are spaced wider can use the Wolfcamp design at higher price decks

          The model is also picking up on the thinning Wolfcamp A-XY interval as a dominant factor. When wells are within the thinner part of the basin the downward impact of up-sized Wolfcamp completions doubles which is driving the model to veer towards the smaller 3rd Bone Spring completion design.

          The larger designs have an increased negative impact when there is a thinner Wolfcamp A-XY compared to the smaller design

          How much value is added through optimization of the development strategy?

          When using this new optimized development strategy of the lower Bone Spring design on all 55 DUCs in Noble’s inventory we can cut capital costs by ~$168MM and increase the NPV10 of these DUCs by $112MM at a $20 flat oil price.

          Conclusions

          • It makes pragmatic sense to complete through DUC inventory as capital budgets have been slashed and drilling rigs have been laid down.
          • According to Enverus data, NBL has 55 current DUCs in the Delaware basin and has historically completed these wells with two different designs for different formations.
          • Other operators in the area have been using more fluid in their designs; however, the Novi model sees that the the additional cost for fluid does not seem to be worth the increased production.
          • Under Noble’s current completion designs, the capital costs to complete through the DUC inventory in the Delaware would be close to ~$302MM.
          • At $20 flat oil price the lower Bone Spring design becomes the most economic for the entire inventory.
          • At higher price decks, wider spaced wells benefit from the traditional Wolfcamp design, but all tightly spaced wells are more economic at smaller completion designs. NBL should be tuning the completion designs to the spacing they intend to implement in each section.
          • Noble can save ~$168MM on capital costs and increase NPV10 of these DUCs by $112MM if they switch to the lower completion design across the entire DUC inventory.
          • NBL should consider reducing completion job sizes given the short term impact on cash as they complete through their inventory.

          Analysis like this can be used to further study and drive better business decisions to maximize returns. If you would like to learn more about our software or have questions about this analysis, drop us a line and we will get in touch.

          Filed Under: Big Data Management, Machine Learning in Oil and Gas Blog Tagged With: QEP, Midland, Permian, Prediction Engine, Masters Series

          Previous postchange of plans: how QEP could optimize returns in their Midland asset in a low-price environment
          Next postthe confidence game: optimizing completions for XEC DUC wells in the Delaware using model confidence as a proxy for risk
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          • This field is for validation purposes and should be left unchanged.

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