Formation evaluation using wavelet analysis on logs of the Chinji and Nagri Formations, northern Pakistan

摘要

The relatively new method of using wavelets in well log analysis is a powerful tool fordefining multiple superimposed scales of lithic trends and contacts. Interpretingdepositional processes associated with different scales of vertical variation within welllog responses allows prediction of the lateral extent of sands and the distribution ofinternal flow barriers important for development of oil field recovery strategies.Wavelet analysis of grain-size variations in a 2.1 km thick fluvial sectionincluding the fluvial Chinji and Nagri Formations, northern Pakistan, revealed threemajor wavelengths. Reliability of the wavelength values was tested and confirmed bymultiple sectioning of the dataset. These dominant wavelengths are interpreted to reflectvertical variations within individual channels, the stacking of channel belts withinoverbank successions due to river avulsion, and larger-scale channel stacking patternswithin this foreland basin that may reflect allocyclic influences. Wavelet analysis allowsquantification of the scales of periodic vertical variations that may not be strictly cyclic innature.Comparison of total wavelet energies over all scales for each depth to the grainsize and sand percentages yielded good correlations with sand proportion curves.Although changes in the wavelet energy profile were much more distinct with respect tograin size, lithic boundaries' locations were not detected based solely on the total of thewavelet energies.The data were also analyzed using Fourier transforms. Although Fouriertransforms of the data yielded the smallest scale cyclicities, the higher-order cyclicities were not defined. This comparison demonstrates the power of wavelet analysis indefining types of repetitive, but not strictly cyclic, variations that are commonly observedin the sedimentary record.Assessments of Milankovitch cyclicities were performed for the Chinji and theNagri Formations using statistical and analytical analysis methods. A clear matchbetween Milankovitch frequency ratios and vertical lithic variations was not observed,and thus distinct climatic control on cyclic lithological trends was not demonstrated.Analysis using wavelets to determine wavelet coefficients helps quantifycharacteristic scales of vertical variations, cyclicities, zone thicknesses, and locations ofabrupt lithic boundaries. Wavelet analysis provides methods that could be used to helpautomate well log analysis.