Definitive Indicators of Hydrocarbon Production Character in Horizontal Shale Exploration.
The practice of characterizing the nature of produced hydrocarbons from mud gas data using Component analysis has been common for over 70 years(*). A popular component analysis method is a set of ratios known as Wetness, Character, and Balance equations. For a vertical well drilled in conventional reservoirs, inferences were drawn from these ratios related to pay intervals of the well. The interpretive guideline for that ratio set is prefaced upon analysis of a production gas sample using laboratory equipment, conditions and protocols, including QA/QC. The drilling environment, inferior equipment, protocols, and the sample differences in the field simply do not match lab precision and quality. This may explain the mixed results in the use of these techniques for the characterization of hydrocarbon zones and the prominent skepticism of the resulting indications. The introduction of direct quadrupole mass spectrometry (DQMS) and its field application on horizontal wells has shown positive results in the application of these traditional component ratios using the significantly better precision and more linear data of the DQMS. The gas data reported here was collected using the Divining Quad 1000 TM from Fluid Inclusion Technologies, Inc. TM. The DQ 1000 TM produces data which is essentially linear through 7+ orders of magnitude and reflects reasonably accurate determinations of concentrations for CI through CIO, which can then be used in component ratio calculations, yielding more consistent scores. This study demonstrates an analytical use of DQMS-derived component ratios. In this study, the component ratio application is used to predict the production character of horizontal shale wells. When performed on DQMS-derived data, scores for component ratios are shown to confidently differentiate shale wells that will produce significant liquids. In these shale exploration laterals, guidelines for the interpretation of DQMS-derived component ratios are directly suggested by the data itself.
AAPG Search and Discovery Article #90152©2012 AAPG Southwest Section Meeting, Fort Worth, Texas, 19-22 May 2012