Estimation of seismic attenuation for reservoirs mapping and inverse Q‐filtering: An application on land seismic data

Abstract

Seismic attenuation values based on inverse Q-filtering are useful in enhancing seismic data resolution for quantitative interpretation. However, as field attenuation estimations are often contaminated by noise and overburden effects, an inverse Q-filter may reduce the signal-to-noise ratio. To help reservoir mapping with seismic resolution enhancement, we use well logs and surface seismic data to estimate the attenuation of a depth interval composed of several carbonate oil reservoirs onshore the Arabian Peninsula. From applying a prestack Q inversion on τ-p gathers from a large 3D seismic survey, the estimated effective attenuation values show spatially coherent patterns, likely corresponding to changes in the petrophysical and fluid properties. The patterns of the estimated effective attenuation values correlate considerably with the anticline geometry, with higher values on its crest than its flanks. The small percentage of the negative effective attenuation values indicates that the apparent attenuation and overburden effects are insignificant. At well locations, the effective attenuation values show a good correlation with the average porosity of the main reservoir, verifying that they are related to changes in petrophysical properties in the analysis interval. We propose an extended inverse Q-filter with two additional parameters to make it more robust and flexible and test it with synthetic and field datasets. We estimate a multiple-scattering attenuation value from well logs and use it in the proposed filter for the field dataset. The compensation for the multiple-scattering effects suppresses the overprints of the data components unrelated to the target interval, hence benefitting the quantitative data interpretation.

Hydrocarbon Reservoir Characterization in the Challenging Structural Setting of Southern Gulf of Suez: Synergistic Approach of Well Log Analyses and 2D Seismic Data Interpretation

“…The main goal of fault interpretation is to identify and characterize fault zones that may affect the spatial distribution of underlying geological formations, as stated by [64]. Velocity Modelling and Depth Conversion are essential for estimating the distribution of subsurface velocity based on seismic data [65]. Well log data integration is commonly used to align and verify the seismic interpretation, as stated by [8,64].…”

Multichannel seismic data attenuation compensation via curvelet‐based sparsity promotion

“…(2020) proposed an extended stabilization factor by introducing hyper‐parameters and an adaptive gain limit to achieve a desirable high‐resolution compensation result. Alshangiti and Zhou (2023) developed another extended stabilized inverse Q filter by adding two additional parameters and applied it to 3D field data attenuation compensation. Tian et al.…”

“…Li et al (2020) proposed an extended stabilization factor by introducing hyper-parameters and an adaptive gain limit to achieve a desirable high-resolution compensation result. Alshangiti and Zhou (2023) developed another extended stabilized inverse Q filter by adding two additional parameters and applied it to 3D field data attenuation compensation. Tian et al (2023) proposed a new variable stabilization factor that dynamically changes with travel time, frequency, signal-to-noise ratio and quality factor to improve the compensation stability to some extent.…”