AVAZ Analysis Research Articles

Characterization of seismic anisotropy using azimuthal AVO analysis (AVAz) - An application case study in the deep and tight carbonate reservoirs from Potwar Basin onshore Pakistan

Reliable characterization of subsurface fractures information within the carbonate's resources plays a key role in reservoir description in terms of the storage and movement of fluid. Commonly, anisotropy information classifies heterogeneity in the rock fabric due to fractures, pores, and local stress variations. Amplitude Variation with Azimuth investigation examines azimuthal variations in the seismic amplitude information to provide useful information about fractures and anisotropy of a horizontally transverse isotropic (HTI).This paper presents modeling, analysis, and interpretation of Azimuthal amplitude variation with angles (AVAz) from 3D seismic and calibrate results with the wells data to extract fractures information in terms of fractures magnitude and orientations. We employed two most used data-driven alternate approaches 1) near-offset Rüger's equation and 2) azimuthal Fourier Coefficient (FC) for analyzing the AVAz responses in seismic data to estimate the fractures density and their orientations, and results are calibrated with the bore hole image data (FMI). These approaches proved practically convenient to quantify the azimuthal amplitude variations with two sets of AVAZ attributes. The results of AVAz modeling and analysis required good quality of input data. Before AVAZ modeling and attributes analysis, seismic data is pre-conditioned, and the data quality of the 3D seismic dataset is improved. Several qualitative and quantitative QC measures (e.g., comparison of angle stacks, AVAz analysis, cross-plots of correlation coefficients, and time shifts) are employed to ascertain the improvement of the health of the seismic data. Azimuthal AVA modeling helped to understand the azimuthal amplitude response due to anisotropy caused by fractures/stress. The predicted seismic response from the models is used to assess the sensitivity of AVAZ with the parameters of the anisotropic model. After the AVAZ modeling, the outcomes of the AVAZ attributes are generated using to 3D seismic and calibrated with the well data set to identify the anomaly of anisotropic gradient (Bani) and second Fourier coefficients (R2) by relating to fractures density or stress magnitude. These attributes helped to identify the amplitude variations with offset and azimuth in the deep inhomogeneous tight carbonate reservoir interval (Patala) of DS hydrocarbon field discovered in the north Potwar Basin, onshore Pakistan. High score of Bani or R2 observed at well location at the tight Paleocene carbonate (Patala formation) reservoirs exhibited the presence of fractures which is confirmed from the image logs (e.g., FMI).The results demonstrated that the studied formations exhibit significant heterogeneity due to the faults/fractures and stresses associated with the complex geological structure of the basin as well as variations in the rock fabric. Hence, accurate analysis of the fractures information from seismic data is quite useful not only in understanding the reservoir heterogeneity to optimize the production, but also in predicting the completion and development strategies that may be most effective.

Preconditioning seismic data with 5D interpolation for computing geometric attributes

The most common preconditioning of seismic data improves the signal-to-noise (S/N) ratio of the seismic data by removing spatial noise or enhancing the coherency and alignment of the reflection events, without unnecessary smoothing or smearing of the discontinuities. Although we usually think of removing unwanted features, we can also improve the S/N by predicting unmeasured signal, such as dead traces and lower-fold areas corresponding to unrecorded offsets and azimuths in the gathers. Missing offsets and azimuths almost always negatively impact prestack inversion and AVAz analysis. While missing offsets and azimuths may not result in sufficiently reduced S/N of stacked data to impair conventional time-structure interpretation, they usually give rise to attribute artifacts. If the inconsistencies in fold follow a regular pattern, we refer to the corresponding attribute pattern as “acquisition footprint.” Acquisition footprint is an undesirable artifact that masks the geologic features or amplitude variations seen on time slices from the seismic data, especially at shallow times. We begin our article by correlating missing data and areas of low fold to artifacts seen in seismic attributes. We then show how 5D interpolation of missing data prior to prestack migration results in more complete gathers resulting in a better balanced stack and the reduction of footprint and other attribute artifacts.

Recent advances in determination of fracture strike and crack density fromP-wave seismic data

Confidence in the ability of AVAZ analysis (amplitude variation with angle and azimuth) to capture information about fractures in a reservoir has steadily increased over the last four years because this technique detected seismic anisotropy in many different reservoirs and the results consistently tied other information about fractures.