Estimation of Parigi reservoir characteristics using seismic attributes, AVO analysis and AVO inversion, and seismic inversion

1995 ◽  
Author(s):  
Djoko Santoso ◽  
Alfian ◽  
Lilik Hendrajaya ◽  
Joel S. Watkins ◽  
Syamsu Alam ◽  
...  
Keyword(s):  
Seismic Attributes ◽  
Seismic Inversion ◽  
Avo Analysis ◽  
Reservoir Characteristics ◽  
Avo Inversion

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

Introduction to this special section: AVO inversion

2019 ◽  
Vol 38 (10) ◽  
pp. 752-753
Author(s):  
Edward Townend ◽  
Michael Kemper
Keyword(s):  
Case Studies ◽  
Best Practice ◽  
Special Section ◽  
Leading Edge ◽  
Seismic Inversion ◽  
The Body ◽  
Amplitude Variation With Offset ◽  
Field Development ◽  
Avo Inversion ◽  
The Subject

It has been more than three years since The Leading Edge last published a special section on amplitude variation with offset (AVO) inversion, and interest in the subject remains strong. This past spring, SEG hosted a joint symposium in Houston, Texas, on the “Resurgence of seismic inversion,” and the body of talks and case studies demonstrated the method's continued relevance to making impactful drilling decisions. Despite this, and despite AVO inversion's position as a mature and well-established technique, there are an abundance of examples in which inaccurate AVO predictions have led to drastic failures at the drill bit. This highlights the challenges that still exist in the successful execution of such investigations and makes the subject occasionally controversial and certainly fraught with data-quality and best-practice considerations. In this vein, the special section presented here offers examples of the broad sweep of considerations and methods relevant to enabling successful AVO inversion and the interpretation of its products, as well as case studies that demonstrate how application of the technique can be impactful all the way through to appraisal and field development programs.

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.

scholarly journals Porosity Prediction Using Neural Network Based on Seismic Inversion and Seismic Attributes

2019 ◽  
Vol 125 ◽  
pp. 15006
Author(s):  
Taufik Mawardi Sinaga ◽  
M. Syamsu Rosid ◽  
M. Wahdanadi Haidar
Keyword(s):  
Neural Network ◽  
Probabilistic Neural Network ◽  
Average Frequency ◽  
Seismic Attributes ◽  
Seismic Inversion ◽  
Carbonate Reservoir ◽  
Neural Network Method ◽  
Time Migration ◽  
The Neural Network ◽  
Network Method

It has done a study of porosity prediction by using neural network. The study uses 2D seismic data post-stack time migration (PSTM) and 2 well data at field “T”. The objective is determining distribution of porosity. Porosity in carbonate reservoir is actually heterogeneous, complex and random. To face the complexity the neural network method has been implemented. The neural network algorithm uses probabilistic neural network based on best seismic attributes. It has been selected by using multi-attribute method with has high correlation. The best attributes which have been selected are amplitude envelope, average frequency, amplitude weighted phase, integrated absolute amplitude, acoustic impedance, and dominant frequency. The attribute is used as input to probabilistic neural network method process. The result porosity prediction based on probabilistic neural network use non-linear equation obtained high correlation coefficient 0.86 and approach actual log. The result has a better correlation than using multi-attribute method with correlation 0.58. The value of distribution porosity is 0.05–0.3 and it indicates the heterogeneous porosity distribution generally from the bottom to up are decreasing value.

scholarly journals Identification of nonstructural type traps within the limits of northern side of Dnieper-Donets Depression according to the data of AVO analysis and seismic inversion

2021 ◽  
Vol 43 (2) ◽  
pp. 227-235
Author(s):  
I.L. Mikhalevich ◽  
P.M. Kuzmenko ◽  
A.P. Tishchenko ◽  
A.S. Vyzhva ◽  
S.A. Vyzhva
Keyword(s):  
Wave Field ◽  
Dynamic Characteristics ◽  
Sedimentary Cover ◽  
Seismic Signal ◽  
Seismic Inversion ◽  
Geological Structure ◽  
Avo Analysis ◽  
Geophysical Surveys ◽  
Northern Side

Nonstructural type traps in the sedimentary cover of the northern side of the Dnieper-Donets depression are poorly studied by seismic methods due to many factors among which are the following: complicated geological structure and not so high quality of given data of geological-geophysical studies of last years. Identification of lithologically screened gas-saturated object has been demonstrated based on the studies of elastic dynamic characteristics by the methods of AVO-analysis and elastic seismic inversion. Acoustic and elastic properties have been analyzed in the wells with cross-dipole real and synthesized acoustics. Gas-saturated intervals have been identified based on the ratios VP /VS and acoustic impedance. According to AVO-studies within the northern side of DDD in the stratum of productive horizons of the moscovian horizon a positive answer has been obtained to the question «if AVO analysis works correctly in general within the limits of the northern side of DDD deposits». Determining factors that influence on the result during the application of AVO-analysis at the most part of gas condensate field of the northern side of DDD are effective thicknesses, depths of occurrence, lithology, poro-sity and quality of given seismic data and data from geophysical surveys of wells. Taking into account minor effective thicknesses, small values of porosity, significant depths of occurrence of productive layers typical for the northern side of DDD, the majority of gas-saturated intervals are not at all identified in the wave field by dynamic characteristics of seismic signal. All the seismic anomalies analyzed had effective thicknesses from 6 to 20 m. Within the limits of deposits of the northern side of DDD, AVO-anomalies of the 2nd class are modeled. Along with positive experience of identification of dynamically cont-rasting objects in the wave field limitations to use methods of AVO-analysis and elastic seismic inversion are generalized for the northern side shown in particular and the whole Dnieper-Donets depression.

Characterizing complex slope channel reservoirs applying extended elastic impedance, Saffron gas field, offshore Nile Delta, Egypt

2021 ◽  
Vol 40 (2) ◽  
pp. 151a1-151a7
Author(s):  
Adel Othman ◽  
Ahmed Ali ◽  
Mohamed Fathi ◽  
Farouk Metwally
Keyword(s):  
Water Saturation ◽  
Nile Delta ◽  
Seismic Attributes ◽  
Significant Degree ◽  
Seismic Inversion ◽  
Gas Field ◽  
Amplitude Variation With Offset ◽  
3D Volume ◽  
Elastic Impedance ◽  
Sand Bodies

In a complex reservoir with a significant degree of heterogeneity, it is a challenge to characterize the reservoir using different seismic attributes based on available data within certain time constraints. Prestack seismic inversion and amplitude variation with offset are among the techniques that give excellent results, particularly for gas-bearing clastic reservoir delineation because of the remarkable contrast between the latter and the surrounding rocks. Challenges arise when a shortage of seismic or well data presents an obstacle in applying these techniques. A further challenge arises if it is necessary to predict water saturation (Sw) using the seismic data because of the independent nonlinear relationship between Sw and seismic attributes and inversion products. Prediction of Sw is necessary not only for characterizing pay from nonpay reservoirs but also for economic reasons. Therefore, extended elastic impedance has been performed to produce a 3D volume of Sw over the reservoir interval. Then, a 3D sweetness volume and spectral decomposition volumes were used to grasp the geometry of the sand bodies that have been charged with gas in addition to their connectivity. This could help illustrate the different stages in the evolution of the Saffron channel system and the sand bodies distribution, both vertically and spatially, and consequently increase production and decrease development risk.

Seismic Attributes and Acoustic Inversion for Shallow Marine Slope Stratigraphy Analysis

2021 ◽  
Author(s):  
Jungrak Son ◽  
Rebecca Boon ◽  
Julien Kuhn de Chizelle
Keyword(s):  
Signal Processing ◽  
Site Characterization ◽  
Seismic Attributes ◽  
Offshore Structures ◽  
Seismic Inversion ◽  
Shallow Marine ◽  
Time Domain Data ◽  
Geological Features ◽  
Marine Site ◽  
The Hilbert Transform

Abstract Geophysical seismic surveys have been used in marine site characterization for subsea engineering and the design of offshore structures. Signal processing plays a key role in obtaining seismic attributes from observed seismic data to identify subsurface geological features within complex shallow sediments. Instantaneous amplitude, phase, and frequency are the most widely used seismic attributes to indicate geological features, but those time-domain data are too limited to define an accurate subsurface model in depth. Therefore, seismic inversion is also required to generate additional geospatial subsurface model information to aid in shallow stratigraphy interpretation. In this paper, we applied both geophysical signal processing and stochastic seismic inversion to a high-resolution multichannel seismic dataset from the Eastern North American Margin (ENAM). Seismic attributes from the Hilbert transform and inversion modeling results (acoustic impedance and modeling uncertainty) were integrated to define better geological horizons and discontinuities. The results show the integrated geophysical subsurface models can support seismic interpretation and improve shallow marine site characterization.

Seismic attribute driven integrated characterization of the Woodford Shale in west-central Oklahoma

2013 ◽  
Vol 1 (2) ◽  
pp. SB85-SB96 ◽  
Author(s):  
Nabanita Gupta ◽  
Supratik Sarkar ◽  
Kurt J. Marfurt
Keyword(s):  
Seismic Attributes ◽  
Seismic Inversion ◽  
Organic Content ◽  
Tectonic Deformation ◽  
Well Performance ◽  
Woodford Shale ◽  
Seismic Attribute ◽  
Well Completion ◽  
West Central ◽  
Basin Floor

The organic-rich, silty Woodford Shale in west-central Oklahoma is a prolific resource play producing gas and liquid hydrocarbons. We calibrated seismic attributes and prestack inversion using well logs and core information within a seismic geomorphologic framework to define the overall basin architecture, major stratigraphic changes, and related variations in lithologies. Core measurements of elastic moduli and total organic content (TOC) indicated that the Woodford Shale can be broken into three elastic petrotypes important to well completion and hydrocarbon enrichment. Upscaling these measurements facilitates regional mapping of petrotypes from prestack seismic inversion of surface data. Seismic attributes highlight rugged topography of the basin floor of the Paleo Woodford Sea, which controls the lateral and vertical distribution of different lithofacies containing variable quantity of TOC as well as quartz, which controls brittleness. Depressions on the basin floor contain TOC-lean cherty lithofacies alternating with TOC-rich lithofacies, resulting in brittle-ductile rock couplets. In contrast, basin floor highs are characterized by overall TOC-rich ductile lithofacies. Seismic attributes illuminate complex post-Woodford tectonic deformation. The Woodford Shale is known to be naturally fractured on outcrop. Image log analysis in other shale plays showed a good correlation between such tectonic features and natural fractures. These features need to be correlated with well trajectories and production data to determine which hypothesized “fracture sets,” if any, improve well performance.

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