Characterization of secondary reservoir potential via seismic inversion and attribute analysis: A case study

Ali, Aamir; Younas, Muhammad; Ullah, Matee; Hussain, M.; Toqeer, Muhammad; Bhatti, Asher Samuel; Khan, Azhar Abbas

doi:10.1016/j.petrol.2019.03.039

Cited by 15 publications

(4 citation statements)

References 19 publications

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“…The seismic post stack impedance inversion can be utilized to extract spatial distribution of reservoir properties e.g., ϕ via geostatistical relationships (Ali et al, 2018), but the focus of this study is on static modelling to obtain the spatial distribution of different complex reservoir properties i.e., ϕ and S w . Furthermore, except porosity the spatial distribution of reservoir properties like S w via seismic post stack impedance inversion can be highly questionable (Ali et al, 2019), however, that is not the case for static modelling.…”

Section: Model Based Inversionmentioning

confidence: 99%

“…Key lithologic horizons identified on seismic reflection data are correlated to well data either by generating synthetic seismograms, check shot surveys or by a vertical seismic profiling (Cubizolle et al, 2015;Ali and Farid, 2016;Wu and Caumon, 2017). Utilizing the results of studies from well data to predict and map reservoir properties over large areas can provide a guide for the reservoir modelling procedure (Ali et al, 2018(Ali et al, , 2019.…”

Section: Introductionmentioning

confidence: 99%

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3D static reservoir modelling to evaluate petroleum potential of Goru C-Interval sands in Sawan Gas Field, Pakistan

2023

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This study is aimed at building a 3D static model of the C-Interval horizon within the Lower Goru Formation of the Sawan gas field, Pakistan. The C-Interval horizon is a proven gas reservoir with considerable potential for further development. Sequence stratigraphic interpretation reveals that C-Interval horizon was deposited under transgressive-regressive conditions, with forced regression resulting in deposition of sand bodies in a deltaic environment. Well logs and core analysis reveal different lithological facies. Thin interbedded shales induced extreme heterogeneity in C-Interval reservoir properties. Sequential Indicator Simulation (SIS) and Sequential Gaussian Simulation (SGS) have been applied to spatially map the heterogeneities of the reservoir properties such as water saturation (S w ), porosity (ϕ), facies, etc. The models indicate thick reservoir quality sand facies are present in the northeastern half with high effective porosity (ϕ e ) being consistent with the high sand content near the paleo-coast line. However, the shale content (V sh ) increases towards the southwestern half consistent with more basinward settings. The lithologies in the southwestern half exhibit low ϕ e with an increase in S w . The techniques utilized in this study have implications for other producing hydrocarbon fields with complex reservoir properties and similar geological settings.

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Section: Model Based Inversionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

3D static reservoir modelling to evaluate petroleum potential of Goru C-Interval sands in Sawan Gas Field, Pakistan

2023

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“…The early proven small gas reservoirs in the eastern belt around the Penyijingxi sag of the Junggar Basin, such as the Pen 5, Mobei 2, and Mobei 5 gas reservoirs, are all secondary hydrocarbon reservoirs formed by the re-accumulation of primary oil and gas reservoirs after damage and adjustment [31,32]. The phenomenon of damage and adjustment of such primary oil and gas reservoirs also occurs in the Tarim Basin, the Sichuan Basin, the Georgina Basin, the Lower Indus Basin, and other structurally active basins [33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Genesis Types and Migration of Middle and Lower Assemblages of Natural Gas in the Eastern Belt around the Penyijingxi Sag of the Junggar Basin, NW China

Liu

Zhang

et al. 2023

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This study analyzes the geochemical characteristics of natural gas composition, carbon isotope, and light hydrocarbon in the eastern belt around the Penyijingxi sag of the Junggar Basin. The result shows the that natural gas content is dominated by alkane gas, with low contents of heavy hydrocarbon and non-hydrocarbon components. The overall carbon isotopic composition of the alkanes shows a trend as δ13methane (C1) < δ13ethane (C2) < δ13propane (C3) < δ13butane (C4), and all δ13C1 values are <−30‰, which are typical of gases of organic origin. The natural gas is mainly coal-derived gas from the Lower Urho formation, mixed with a small amount of oil-associated gas from the Fengcheng formation. The vertical migration of natural gas resulted in the mixing of oil-associated gas and coal-derived gas and the mixing of alkane gas at different stages of the same origin, which should be the origin of carbon isotope inversion. The diffusion migration of carboniferous oil and gas reservoirs has led to differences in gas geochemical characteristics among gas wells. These migration characteristics of natural gas may indicate that the shallow layers are a favorable stratum for the next step of oil and gas exploration in the eastern belt around the Penyijingxi sag.

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“…The reservoir characterization and limestone formations were delineated via seismic instantaneous amplitude, frequency and phase by imaging various target units (Farfour et al 2015). (Ali et al 2019) used the dominant frequency attribute to define the characterization of hydrocarbon bearing reservoir. (Verma et al 2018) inferred the dunal and interdunal deposits in 3D seismic data volume through the combination of coherence attribute and inverted Pimpedance.…”

Section: Introductionmentioning

confidence: 99%

Seismic attributes via robust and high-resolution seismic complex trace analysis

2020

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Seismic attributes calculated by conventional methods are susceptible to noise. Conventional filtering reduces the noise in the cost of losing the spectral bandwidth. The challenge of having a high-resolution and robust signal processing tool motivated us to propose a sparse time-frequency decomposition while is stabilized for random noise. The procedure initiates by using Sparsity-based adaptive S-transform to regularize abrupt variations in frequency content of the nonstationary signals. Then, considering the fact that a higher amplitude of a frequency component results in a higher signal to noise ratio, an adaptive filter is applied to the time-frequency spectrum which is sparcified previously. The proposed zero adaptive filter enhances the high amplitude frequency components while suppresses the lower ones. The performance of the proposed method is compared to the sparse S-transform and the robust window Hilbert transform in estimation of instantaneous attributes by applying on synthetic and real data sets. Seismic attributes estimated by the proposed method is superior to the conventional ones in terms of its robustness and high resolution image. The proposed approach has a vast application in interpretation and identification of geological structures.

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Characterization of secondary reservoir potential via seismic inversion and attribute analysis: A case study

Cited by 15 publications

References 19 publications

3D static reservoir modelling to evaluate petroleum potential of Goru C-Interval sands in Sawan Gas Field, Pakistan

3D static reservoir modelling to evaluate petroleum potential of Goru C-Interval sands in Sawan Gas Field, Pakistan

Genesis Types and Migration of Middle and Lower Assemblages of Natural Gas in the Eastern Belt around the Penyijingxi Sag of the Junggar Basin, NW China

Seismic attributes via robust and high-resolution seismic complex trace analysis

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