Abstract
In the last ten years, the production for unconventional, shale, plays is becoming increasingly important. During the development phase, multiple wells are drilled in a single section and the production from adjacent wells can vary significantly. Based on this observation, there is a notion in the oil and gas industry that horizontal wells drilled in shale plays appear to be random in nature; i.e., the production from adjacent wells show no apparent correlation. This lack of correlation is attributed to the variability of the hydraulic fractures, ignoring the underlying geology. The current SPEE (Society of Petroleum Engineering Evaluation Engineers) monograph (SPEE, 2011) on reserve estimation implicitly assumes the performance of adjacent wells to be randomly correlated.
This study questions the SPEE approach and provides an alternative methodology for evaluating reserves from unconventional formations. We perform a case study on the Eagle Ford shale formation in south and central Texas and the issue of the underlying geological continuity is addressed by properly accounting for the scale. The key difference between vertical and horizontal wells is that vertical wells’ performance can be closely tied to the core and log data collected at the well location as the productivity of the well can be correlated to the information at the well. Horizontal wells differ significantly from vertical wells since the log data collected from the vertical portion of the well and the production obtained from the horizontal wells come from different parts of the reservoir. The only way we can correlate the log response data to the horizontal well production data is by scaling the data appropriately which is done by averaging the production data around the horizontal well location. Thus, this recalibrated production data represents the productivity around that region. Geostatistics provides the necessary tools to properly scale the initial potential from the horizontal wells. In addition to scaling the production data, we also scale the well log data and compare the scaled well log data to production data. The correlation between the two clearly illustrates that there is an underlying relationship between the log data collected and the potential of the wells. Using this developed relationship, it is demonstrated that geology matters in high grading the well locations in shale plays. The uncertainty about the performance of the horizontal wells can be significantly reduced by using the well log information that will help interpret the well performance at each un-drilled location. Future predictions of well performance made using this model indicates that the method is successful in correctly predicting the performance of future wells. Although the methodology is only applied to Eagle Ford data, it can be easily adapted to other shale plays.
