Selection of Sensitive Post-Stack and Pre-Stack Seismic Inversion Attributes for Improved Characterization of Thin Gas-Bearing Sands

Shakir, Urooj; Ali, Aamir; Hussain, Muyyassar; Azeem, Tahir; Bashir, Lamuail

doi:10.1007/s00024-021-02900-1

Cited by 10 publications

(5 citation statements)

References 43 publications

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“…Accurately delineating stratigraphic and structural traps requires a thorough understanding of subsurface configurations. The seismic data show the existence of a thrusted anticline with accompanying thrust faults [23]. The seismic profile reveals two prominent structures in the study area: the Zamzama structure in the south and the Mehar structure in the north.…”

Section: Seismic Data Structural Interpretationmentioning

confidence: 85%

“…This uplift caused thick deposition of the Sembar and Lower Goru formations along the passive margin, which acted as the primary source for the overlying sand reservoirs. The sands of the Lower Ranikot Formation were also deposited in these environments [22][23][24][25][26][27], which are the main target reservoirs in the Mehar Gas Field.…”

Section: Tectonics Geology and Stratigraphy Of The Study Areamentioning

confidence: 99%

“…FIGURE 2: In a stratigraphic column, the generalized stratigraphic column of the Central Indus Basin with the main hydrocarbon field in which depth is measured in meters[22,23].…”

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confidence: 99%

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Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis

Ehsan,

Zaheer,

Abbasi

2024

Journal of GeoEnergy

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An approach is proposed to improve modeling for shale gas reservoirs, integrating key parameters such as total organic carbon (TOC) and porosity. Seismic inversion uses seismic reflection data and well-log information to improve geological and geophysical interpretation and estimate rock properties with high-resolution subsurface acoustic impedance, including low and high frequencies. The Ranikot Formation in the Central Indus Basin, Pakistan, is a Paleocene-age formation with the potential to act as reservoir, seal, and source rock. The porosity of the Lower Ranikot reservoir in the Mehar Block was calculated using seismic inversion analysis with the Mehar-02 well. The petrophysical analysis yielded an effective porosity of 5.8%. Similarly, when calculated using seismic inversion, the porosity fell within the 5.5%–6.0% range. Determining the TOC content is crucial in evaluating unconventional shale resources. Petrophysical approaches, such as the ΔlogR method, offer a fast, convenient, and cost-effective means of estimating TOC from well logs. This method is commonly used in conventional source rock evaluation and applied to unconventional resource play evaluation. On the other hand, seismic inversion techniques were used to conduct TOC analysis in the absence of core data in order to estimate the source potential of the Upper Ranikot Formation. To estimate the TOC log for the Upper Ranikot shales in the Mehar Block, the Passey equation was used on the well logs of the Mehar-02 well. The estimated TOC for the Upper Ranikot shales is around 2.0%, which falls within the fair TOC range.

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Section: Seismic Data Structural Interpretationmentioning

confidence: 85%

Section: Tectonics Geology and Stratigraphy Of The Study Areamentioning

confidence: 99%

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Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis

Ehsan,

Zaheer,

Abbasi

2024

Journal of GeoEnergy

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“…Thin layers commonly exhibit heterogeneous structures (e.g., Hussain et al., 2023; Li et al., 2020), such as internal stratification (Figure 1a), which, in turn, govern their effective seismic response. Pertinent applications of reflectivity studies on thin layers are, for instance, the characterization of gas‐bearing beds (e.g., Cichostȩpski et al., 2019; Shakir et al., 2022) as well as the monitoring of carbon sequestration (e.g., Williams & Chadwick, 2012; Zhang et al., 2013). Current methodologies to estimate the rock properties of thin layers have been largely developed within the elastic framework (e.g., Huang et al., 2016; Puryear & Castagna, 2008; Romdhane & Querendez, 2014; Rubino & Velis, 2009; Zhang et al., 2013).…”

Section: Introductionmentioning

confidence: 99%

Homogenization of Porous Thin Layers With Internal Stratification for the Estimation of Seismic Reflection Coefficients

Sotelo,

Barbosa,

Solazzi

et al. 2023

JGR Solid Earth

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Stratified thin layers often present a prominent mechanical contrast with regard to the embedding background and, hence, are important targets for seismic reflection studies. An efficient way to study the reflectivity response of these thin layers is to employ their homogenized viscoelastic equivalents. We aim to homogenize a simple, yet realistic, thin‐layer model, which is composed of a finite non‐periodic sequence of homogeneous porous strata embedded in a background deemed impermeable at the seismic frequencies. The overarching objective is to reproduce the reflectivity response of such stratified thin layers. However, the estimation of the equivalent moduli is inherently affected by the boundary conditions (BC) associated with the embedding background. Therefore, classical homogenization procedures, which assume the existence of a periodic structure, are not readily applicable. We, therefore, propose a novel homogenization procedure that incorporates naturally the appropriate BC. To this end, we consider a sample that includes both a part of the background and a section of the thin layer, to which we apply classical oscillatory relaxation tests. However, we estimate the average of stress and strain components only over the thin layer section of interest. To test the accuracy of the method, we consider a sandstone composed of two strata saturated with different fluids embedded in impermeable half‐spaces. After estimating the corresponding equivalent moduli, we compare the resulting P‐wave reflectivities with those obtained using the original model. Our results show that the inferred viscoelastic equivalent closely reproduces the reflectivities of the stratified thin layer in the seismic frequency range.

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“…As the primary method of reservoir quantitative interpretation (Denney, 2013), pre-stack seismic inversion shows strong applicability and effectiveness in parameter estimation. In recent decades, pre-stack inversion has significantly been developed (Buland and Omre, 2003;Downton and Ursenbach, 2006;Buland et al, 2008;Pérez et al, 2013;Grana 2016Grana , 2020Wang et al, 2019;Li et al, 2021), especially for the corresponding parameter inversion used observed seismic reflection data, as widely applied in reservoir exploration (Avseth et al, 2016;Okeugo et al, 2019;Ugbor et al, 2021;Shakir et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Envelope-based constrained model for multiparameter pre-stack seismic inversion

Shan

Yang

et al. 2022

J Petrol Explor Prod Technol

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Pre-stack seismic inversion is an effective method to estimate multiparameter from seismic reflection data in the oil–gas reservoir exploration. In order to get a reliable inverted parameter result, a constrained model is commonly used to reduce the multi-solution in the seismic inversion. However, it is hard to get an appropriate constrained model by conventional well-log data interpolation or velocity field in offshore oil–gas exploration with sparse wells. Envelope inversion has been successfully applied to get a good initial model with low-frequency components in full-waveform inversion. In order to fully exploit the rich information contained in seismic data, we introduce envelope inversion into background modeling based on convolution theory and propose a multiparameter pre-stack seismic inversion with envelope prior constraint. Both inversion results of the model and field data indicate the effectiveness and adaptability of the proposed method in multiparameter estimation.

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Selection of Sensitive Post-Stack and Pre-Stack Seismic Inversion Attributes for Improved Characterization of Thin Gas-Bearing Sands

Cited by 10 publications

References 43 publications

Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis

Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis

Homogenization of Porous Thin Layers With Internal Stratification for the Estimation of Seismic Reflection Coefficients

Envelope-based constrained model for multiparameter pre-stack seismic inversion

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