Shale Play Development Program Using Risk-Reward Mapping from Geospatial Analyses

Abstract

Finding the best drilling locations in an extensive shale play holding is key to achieving production profile expectations and good economic metrics. Shale plays have been described as statistical plays. However, it becomes increasingly unacceptable to drill disappointing, underperforming wells as the operator and partners move from the exploration lifecycle stage into the appraisal and field development stages.The physical and chemical properties of shales dictate the economic success of development drilling programs. It is recognized that at least seven parameters must fall within empirically-determined ranges for a play to have economic production rates and estimated ultimate recovery (EUR) exceeding threshold internal rate of return (IRR) requirements.A geostatistical shale property workflow that high-grades 160-acre sections in a regional shale play, using a limited number of wellbores with standard logging suites is demonstrated. This paper extends the workflow from high-grading drilling targets to quantitative risk assessment. An application of the workflow to a multi-square mile U.S. shale play illustrates the analysis and its interpretation. The example shows that down-spacing well density in high-graded sections (high potential reward) is a quantitatively lower risk investment program than would normally be expected. Typically high reward opportunities, in the investment world, are expected to represent higher risk as well. Geostatistical analysis in the example play shows just the opposite behavior because the statistical nature of the local shale quality can be mapped and profitably drilled.Exploiting this geostatistical, high-grading workflow can accelerate an operator's development program with higher rewards, lower risk, and better rates of return than pursuing a uniform development program over a large regional play.

Optimizing Lateral Lengths in Horizontal Wells for a Heterogeneous Shale Play

“…Area 3 considers the potential for drilling the vertical portion and the first half of the lateral in a good (P 70 > Q > P 90 ) quality quarter-section, with the second half in an average (P 50 > Q > P 70 ) quality quarter-section. As shown by Chorn et al (2013b), an average quality quarter-section production history is approximately one half the cumulative productions achieved in the best-graded quarter-sections. The Area 3 Drilling Location 1 vertical is located at the northern edge of the P 70 > Q > P 90 -grade category quarter-section.…”

“…This architecture is common in the region and is only now evolving to long horizontal wells. The confirmation of the high-grading methodology (Chorn et al 2013b) used production profiles from these vertical wells. As the region's well architecture evolves to using extended lateral lengths to contact more of the reservoir per vertical wellbore, the methodology has been extended to reflect the study area's significant lateral variation in key shale properties.…”

“…For each map, the lateral contacts different amounts of high quality (high production potential shale). Optimizing the number and location of stimulations in each lateral is simply determined by identifying the contact volumes whose shale quality metric is > P 70 , based on the findings of Chorn et al (2013b) for the study area. Table 1 illustrates the relationship between correlation coefficient, shale property quality, and the decision to stimulate for each contacted volume in the two of the three hypothetical property quality maps.…”

“…The economic impact of highgrading has been validated (Chorn et al 2013b) by comparing the results of a drilling program directed by the high-grading analysis versus a program that randomly drilled the study area. A high-graded quarter-section also has a standard deviation of property quality values.…”

Using High-Grading and Portfolio Tools to Allocate Resources among Shale Play Opportunities

“…The variability and distribution of key shale properties are uncertainties as well, but these are uncontrollable. Variability of the properties has not been measurable until recently, but the application of geostatistics and shale well log interpretation technologies are advancing the industry's ability to anticipate where to place wellheads and laterals to access the best shale property combinations (Chorn et al 2013a(Chorn et al , 2013bChorn and Dusterhoft 2014).…”