Characterization of fluvio-deltaic gas reservoirs through AVA deterministic, stochastic, and wave-equation-based seismic inversion: A case study from the Carnarvon Basin, Western Australia

2020 ◽  
Vol 39 (2) ◽  
pp. 92-101
Author(s):  
Arturo Contreras ◽  
Andre Gerhardt ◽  
Paul Spaans ◽  
Matthew Docherty
Keyword(s):  
Wave Equation ◽  
Elastic Properties ◽  
Western Australia ◽  
Mode Conversion ◽  
Seismic Inversion ◽  
Gas Reservoirs ◽  
Amplitude Variation ◽  
Avo Inversion ◽  
Amplitude Data ◽  
Carnarvon Basin

Multiple state-of-the-art inversion methods have been implemented to integrate 3D seismic amplitude data, well logs, geologic information, and spatial variability to produce models of the subsurface. Amplitude variation with angle (AVA) deterministic, stochastic, and wave-equation-based amplitude variation with offset (WEB-AVO) inversion algorithms are used to describe Intra-Triassic Mungaroo gas reservoirs located in the Carnarvon Basin, Western Australia. The interpretation of inverted elastic properties in terms of lithology- and fluid-sensitive attributes from AVA deterministic inversion provides quantitative information about the geomorphology of fluvio-deltaic sediments as well as the delineation of gas reservoirs. AVA stochastic inversion delivers higher resolution realizations than those obtained from standard deterministic methods and allows for uncertainty analysis. Additionally, the cosimulation of petrophysical parameters from elastic properties provides precise 3D models of reservoir properties, such as volume of shale and water saturation, which can be used as part of the static model building process. Internal multiple scattering, transmission effects, and mode conversion (considered as noise in conventional linear inversion) become useful signals in WEB-AVO inversion. WEB-AVO compressibility shows increased sensitivity to residual/live gas discrimination compared to fluid-sensitive attributes obtained with conventional inversions.

Reservoir-oriented wave-equation-based seismic amplitude variation with offset inversion

2017 ◽  
Vol 5 (3) ◽  
pp. SL43-SL56 ◽  
Author(s):  
Dries Gisolf ◽  
Peter R. Haffinger ◽  
Panos Doulgeris
Keyword(s):  
Wave Equation ◽  
Elastic Wave ◽  
Time Lapse ◽  
Background Model ◽  
Nonlinear Inversion ◽  
Elastic Wave Equation ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Avo Inversion ◽  
Object Domain

Wave-equation-based amplitude-variation-with-offset (AVO) inversion solves the full elastic wave equation, for the properties as well as the total wavefield in the object domain, from a set of observations. The relationship between the data and the property set to invert for is essentially nonlinear. This makes wave-equation-based inversion a nonlinear process. One way of visualizing this nonlinearity is by noting that all internal multiple scattering and mode conversions, as well as traveltime differences between the real medium and the background medium, are accounted for by the wave equation. We have developed an iterative solution to this nonlinear inversion problem that seems less likely to be trapped in local minima. The surface recorded data are preconditioned to be more representative for the target interval, by redatuming, or migration. The starting model for the inversion is a very smooth (0–4 Hz) background model constructed from well data. Depending on the data quality, the nonlinear inversion may even update the background model, leading to a broadband solution. Because we are dealing with the elastic wave equation and not a linearized data model in terms of primary reflections, the inversion solves directly for the parameters defining the wave equation: the compressibility (1/bulk modulus) and the shear compliance (1/shear modulus). These parameters are much more directly representative for hydrocarbon saturation, porosity, and lithology, than derived properties such as acoustic and shear impedance that logically follow from the linearized reflectivity model. Because of the strongly nonlinear character of time-lapse effects, wave-equation based AVO inversion is particularly suitable for time-lapse inversion. Our method is presented and illustrated with some synthetic data and three real data case studies.

Nonlinear amplitude-variation-with-offset inversion for Lamé parameters using a direct inversion method

2017 ◽  
Vol 5 (3) ◽  
pp. SL57-SL67 ◽  
Author(s):  
Guangsen Cheng ◽  
Xingyao Yin ◽  
Zhaoyun Zong
Keyword(s):  
Nonlinear Equation ◽  
Real Data ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Nonlinear Inversion ◽  
Reservoir Prediction ◽  
Amplitude Variation ◽  
Linear Inversion ◽  
Amplitude Variation With Offset ◽  
Avo Inversion

Prestack seismic inversion is widely used in fluid indication and reservoir prediction. Compared with linear inversion, nonlinear inversion is more precise and can be applied to high-contrast situations. The inversion results can be affected by the parameters’ sensitivity, so the parameterization of nonlinear equations is very significant. Considering the poor nonlinear amplitude-variation-with-offset (AVO) inversion results of impedance and velocity parameters, we adjust the parameters of the nonlinear equation, avoid the inaccuracy caused by parameters sensitivity and get the ideal nonlinear AVO inversion results of the Lamé parameters. The feasibility and stability of the nonlinear equation based on the Lamé parameters and method are verified by the model and the real data examples. The resolution and the lateral continuity of nonlinear inversion results are better compared with the linear inversion results.

Additional Early Permian ammonoid cephalopods from Western Australia

1990 ◽  
Vol 64 (3) ◽  
pp. 392-399 ◽  
Author(s):  
Brian F. Glenister ◽  
Cathy Baker ◽  
W. M. Furnish ◽  
G. A. Thomas
Keyword(s):  
Western Australia ◽  
Early Permian ◽  
West Texas ◽  
Permian Ammonoid ◽  
Carnarvon Basin

An ancestral paragastrioceratid, Svetlanoceras irwinense (Teichert and Glenister, 1952), and a specifically indeterminate gonioloboceratid, cf. Mescalites sp., from the basal Callytharra Formation are described as the oldest ammonoids recovered from the Permian of the Carnarvon Basin, Western Australia. Identity of these taxa strengthens correlation with the Holmwood Shale (Sakmarian) of the adjacent Perth Basin. Svetlanoceras moylei Mikesh, n. sp., from the Lenox Hills Formation of West Texas, is described for comparison with other simple paragastrioceratids.

Clay mineralogical, geochemical and isotopic tracing of the evolution of the Woodleigh impact structure, Southern Carnarvon Basin, Western Australia

2005 ◽  
Vol 149 (5) ◽  
pp. 576-590 ◽  
Author(s):  
I. Tonguç Uysal ◽  
Arthur J. Mory ◽  
Suzanne D. Golding ◽  
Robert Bolhar ◽  
Kenneth D. Collerson
Keyword(s):  
Western Australia ◽  
Impact Structure ◽  
Isotopic Tracing ◽  
Carnarvon Basin

scholarly journals Gas-bearing sands appraisal for Zamzama Gas field in Pakistan through inverted elastic attributes assisted with PNN approximation of petrophysical properties

2021 ◽  
Author(s):  
Zahid U. Khan ◽  
◽  
Mona Lisa ◽  
Muyyassar Hussain ◽  
Syed A. Ahmed ◽  
...  
Keyword(s):  
Elastic Properties ◽  
Clay Content ◽  
Seismic Inversion ◽  
Indus Basin ◽  
Minimal Risk ◽  
Gas Field ◽  
Lower Indus Basin ◽  
Heterogeneity Effects ◽  
Prestack Seismic Inversion ◽  
Gas Bearing

The Pab Formation of Zamzama block, lying in the Lower Indus Basin of Pakistan, is a prominent gas-producing sand reservoir. The optimized production is limited by water encroachment in producing wells, thus it is required to distinguish the gas-sand facies from the remainder of the wet sands and shales for additional drilling zones. An approach is adopted based on a relation between petrophysical and elastic properties to characterize the prospect locations. Petro-elastic models for the identified facies are generated to discriminate lithologies in their elastic ranges. Several elastic properties, including p-impedance (11,600-12,100 m/s*g/cc), s-impedance (7,000-7,330 m/s*g/cc), and Vp/Vs ratio (1.57-1.62), are calculated from the simultaneous prestack seismic inversion, allowing the identification of gas sands in the field. Furthermore, inverted elastic attributes and well-based lithologies are incorporated into the Bayesian framework to evaluate the probability of gas sands. To better determine reservoir quality, bulk volumes of PHIE and clay are estimated using elastic volumes trained on well logs employing Probabilistic Neural Networking (PNN), which effectively handles heterogeneity effects. The results showed that the channelized gas-sands passing through existing well locations exhibited reduced clay content and maximum effective porosities of 9%, confirming the reservoir's good quality. Such approaches can be widely implemented in producing fields to completely assess litho-facies and achieve maximum production with minimal risk.

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