The application of seismic attributes for reservoir characterization in Pre-Tertiary fractured basement, Vietnam-Malaysia offshore

2014 ◽  
Vol 2 (1) ◽  
pp. SA57-SA66 ◽  
Author(s):  
Nguyen Huy Ngoc ◽  
Sahalan B. Aziz ◽  
Nguyen Anh Duc
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Rock Type ◽  
Seismic Attributes ◽  
Basement Rock ◽  
Fracture Density ◽  
High Fracture ◽  
Offshore Area ◽  
Fracture Characteristics ◽  
Basement Reservoirs

The Pre-Tertiary fractured basement forms important hydrocarbon-bearing reservoirs in the Vietnam-Malaysia offshore area, and is being produced from such reservoirs in Vietnam where the authors have extensive working experiences for both clastics and fractured basement reservoirs and in both exploration and development phases. Due to their very small matrix porosity, the basement rocks become reservoirs only when they are strongly fractured. The quality of the fractured basement reservoirs depends on basement rock type, fracture density, and fracture characteristics including aperture, azimuth, dip, continuity, and fracture system intersection. Three-dimensional seismic data is applied widely to characterize these basement reservoirs. Based on results from applying many different seismic attributes to 3D seismic data from different Pre-Tertiary fractured basements in Vietnam and Malaysia, we demonstrate the utility of attributes in characterizing fractured basement reservoirs. Seismic attributes help predict the basement rock type and fracture characteristics from near top basement to deep inside basement. In the zone near the top of basement, the characteristics of fracture systems can be predicted by amplitude, coherence, curvature, and secondary derivative attributes. Deep inside the basement, relative acoustic impedance and its attributes have been successfully applied to predict the distribution of high fracture density, while dip and azimuth, ant-tracking, and gradient magnitude attributes have proven to be effective for predicting fracture characteristics. The accuracy of fracture characterization based on seismic attributes has been verified by drilling results.

Unsupervised machine learning using 3D seismic data applied to reservoir evaluation and rock type identification

2021 ◽  
pp. 1-69
Author(s):  
Marwa Hussein ◽  
Robert R. Stewart ◽  
Deborah Sacrey ◽  
Jonny Wu ◽  
Rajas Athale
Keyword(s):  
Machine Learning ◽  
Seismic Data ◽  
Rock Type ◽  
Seismic Attributes ◽  
Reservoir Quality ◽  
3D Seismic ◽  
Reservoir Properties ◽  
Unsupervised Machine Learning ◽  
Amplitude Data ◽  
3D Seismic Data

Net reservoir discrimination and rock type identification play vital roles in determining reservoir quality, distribution, and identification of stratigraphic baffles for optimizing drilling plans and economic petroleum recovery. Although it is challenging to discriminate small changes in reservoir properties or identify thin stratigraphic barriers below seismic resolution from conventional seismic amplitude data, we have found that seismic attributes aid in defining the reservoir architecture, properties, and stratigraphic baffles. However, analyzing numerous individual attributes is a time-consuming process and may have limitations for revealing small petrophysical changes within a reservoir. Using the Maui 3D seismic data acquired in offshore Taranaki Basin, New Zealand, we generate typical instantaneous and spectral decomposition seismic attributes that are sensitive to lithologic variations and changes in reservoir properties. Using the most common petrophysical and rock typing classification methods, the rock quality and heterogeneity of the C1 Sand reservoir are studied for four wells located within the 3D seismic volume. We find that integrating the geologic content of a combination of eight spectral instantaneous attribute volumes using an unsupervised machine-learning algorithm (self-organizing maps [SOMs]) results in a classification volume that can highlight reservoir distribution and identify stratigraphic baffles by correlating the SOM clusters with discrete net reservoir and flow-unit logs. We find that SOM classification of natural clusters of multiattribute samples in the attribute space is sensitive to subtle changes within the reservoir’s petrophysical properties. We find that SOM clusters appear to be more sensitive to porosity variations compared with lithologic changes within the reservoir. Thus, this method helps us to understand reservoir quality and heterogeneity in addition to illuminating thin reservoirs and stratigraphic baffles.

Case study: Seismic resolution and reservoir characterization of thin sands using multiattribute analysis and bandwidth extension in the Daqing field, China

2020 ◽  
Vol 8 (1) ◽  
pp. T89-T102
Author(s):  
David Mora ◽  
John Castagna ◽  
Ramses Meza ◽  
Shumin Chen ◽  
Renqi Jiang
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Statistical Significance ◽  
Physical Property ◽  
Seismic Attributes ◽  
Oil Field ◽  
Thin Layers ◽  
Inversion Method ◽  
Bandwidth Extension ◽  
Multiattribute Analysis

The Daqing field, located in the Songliao Basin in northeastern China, is the largest oil field in China. Most production in the Daqing field comes from seismically thin sand bodies with thicknesses between 1 and 15 m. Thus, it is not usually possible to resolve Daqing reservoirs using only conventional seismic data. We have evaluated the effectiveness of seismic multiattribute analysis of bandwidth extended data in resolving and making inferences about these thin layers. Multiattribute analysis uses statistical methods or neural networks to find relationships between well data and seismic attributes to predict some physical property of the earth. This multiattribute analysis was applied separately to conventional seismic data and seismic data that were spectrally broadened using sparse-layer inversion because this inversion method usually increases the vertical resolution of the seismic. Porosity volumes were generated using target porosity logs and conventional seismic attributes, and isofrequency volumes were obtained by spectral decomposition. The resulting resolution, statistical significance, and accuracy in the determination of layer properties were higher for the predictions made using the spectrally broadened volume.

Factors influencing fractures networks within Permian shale intervals in the Cooper Basin, South Australia

2012 ◽  
Vol 52 (1) ◽  
pp. 213 ◽  
Author(s):  
Hani Abul Khair ◽  
Guillaume Backé ◽  
Rosalind King ◽  
Simon Holford ◽  
Mark Tingay ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Positive Curvature ◽  
Seismic Attributes ◽  
Gas Production ◽  
Natural Fracture ◽  
Seismic Survey ◽  
Critical Parameters ◽  
Fracture Density ◽  
High Fracture ◽  
Cooper Basin

The future success of both enhanced (engineered) geothermal systems and shale gas production is reliant on the development of reservoir stimulation strategies that suit the local geo-mechanical conditions of the prospects. The orientation and nature of the in-situ stress field and pre-existing natural fracture networks in the reservoir are among the critical parameters that will control the quality of the stimulation program. This study provides a detailed investigation into the nature and origin of natural fractures in the area covered by the Moomba–Big Lake 3D seismic survey, in the southwest termination of the Nappamerri Trough of the Cooper Basin. These fractures are imaged by both borehole image logs and complex multi-traces seismic attributes (e.g. dip-steered most positive curvature and dip-steered similarity), are pervasive throughout the cube, and exhibit a relatively consistent northwest–southeast orientation. Horizon extraction of the seismic attributes reveal a strong variation in the spatial distribution of the fractures. In the acreage of interest, fracture density is at its highest in the vicinity of faults and on top of tight antiforms. This study also suggests a good correlation between high fracture density and high gamma ray values. The correlation between high fracture density and shale content is somewhat counterintuitive, as shale is expected to have a higher tensile and compressive strengths at shallow depths and typically contain fewer fractures (Lin, 1983). At large depths, however—and due to sandstone diagenesis and cementation—shale has lower tensile and compressive strength than sandstone and is expected to be more fractured (Lin, 1983). A similar correlation has been noted in other Australian Basins (e.g. Northern Perth Basin). Diagenetic effects, pore pressure, stiffness, variations in tensile versus compressive strength of the shale and the sandstone may explain this disparity.

Seismic characterization of a Mississippi Lime resource play in Osage County, Oklahoma, USA

2013 ◽  
Vol 1 (2) ◽  
pp. SB97-SB108 ◽  
Author(s):  
Benjamin L. Dowdell ◽  
J. Tim Kwiatkowski ◽  
Kurt J. Marfurt
Keyword(s):  
Seismic Data ◽  
Seismic Analysis ◽  
High Porosity ◽  
Fracture Density ◽  
Coherent Noise ◽  
High Fracture ◽  
Data Set ◽  
Horizontal Drilling ◽  
Prestack Inversion ◽  
Osage County

With the advent of horizontal drilling and hydraulic fracturing in the Midcontinent, USA, fields once thought to be exhausted are now experiencing renewed exploitation. However, traditional Midcontinent seismic analysis techniques no longer provide satisfactory reservoir characterization for these unconventional plays; new seismic analysis methods are needed to properly characterize these radically innovative play concepts. Time processing and filtering is applied to a raw 3D seismic data set from Osage County, Oklahoma, paying careful attention to velocity analysis, residual statics, and coherent noise filtering. The use of a robust prestack structure-oriented filter and spectral whitening greatly enhances the results. After prestack time migrating the data using a Kirchhoff algorithm, new velocities are picked. A final normal moveout correction is applied using the new velocities, followed by a final prestack structure-oriented filter and spectral whitening. Simultaneous prestack inversion uses the reprocessed and time-migrated seismic data as input, along with a well from within the bounds of the survey. With offsets out to 3048 m and a target depth of approximately 880 m, we can invert for density in addition to P- and S-impedance. Prestack inversion attributes are sensitive to lithology and porosity while surface seismic attributes such as coherence and curvature are sensitive to lateral changes in waveform and structure. We use these attributes in conjunction with interpreted horizontal image logs to identify zones of high porosity and high fracture density.

A new Fourier azimuthal amplitude variation fracture characterization method: Case study in the Haynesville Shale

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. WA101-WA120 ◽  
Author(s):  
Anthony Barone ◽  
Mrinal K. Sen
Keyword(s):  
Seismic Data ◽  
Large Scale ◽  
Rock Fracture ◽  
Crack Density ◽  
Fracture Density ◽  
Success Rates ◽  
High Fracture ◽  
Fracture Characterization ◽  
Free Data ◽  
Seismic Reflectivity

We have evaluated a novel fracture characterization technique using azimuthal amplitude variations (AVAz) present in 3D seismic data, and we implemented it using synthetic and real seismic data targeting the Haynesville Shale. The method we evaluated overcomes many common AVAz limitations and differs from standard AVAz approaches in the following ways: (1) It was explicitly designed to model vertically fractured transverse isotropic (VFTI) media; (2) it can correctly resolve the fracture strike azimuth without a 90° ambiguity and uses a new magnitude-based method that is invariant to the sign of seismic reflectivity [Formula: see text]; and (3) it incorporates advanced inversion techniques to estimate a novel fracture density proxy that responds linearly to crack density. Our method is based on a newly derived relationship that relates seismic reflectivity directly to rock/fracture properties in VFTI media. We validated our method through rigorous testing on more than 400 synthetic seismic data sets. These synthetic tests indicate that our method excels at estimating fracture azimuth and fracture density from surface seismic data with overall success rates around 80%–85% for noisy data and 90%–95% for noise-free data. Applying our method to field data from the Haynesville Shale indicates that the dominant fracture set is oriented at approximately [Formula: see text] relative to geodetic north, i.e., rotated slightly counterclockwise of east–west. We assume a constant azimuth of 80° throughout our relatively small 20 square miles study area, and our method clearly identifies a general area with unusually high fracture density as well as several smaller subzones of dense fracturing. These smaller features appear to be connected by a pervasive large-scale fracture network covering the area with dominant features aligned at roughly parallel and perpendicular to our calculated fracture azimuth. Although we could not directly confirm these fracture characteristics, our results largely agree with previously published information about fracturing in our study area.

scholarly journals Evaluation of seismic attributes for reservoir characterization over Edi field, Niger delta, Nigeria using 3d seismic data

2020 ◽  
Vol 8 (2) ◽  
pp. 168
Author(s):  
Nyeneime O. Etuk ◽  
Mfoniso U. Aka ◽  
Okechukwu A. Agbasi ◽  
Johnson C. Ibuot
Keyword(s):  
Seismic Data ◽  
Niger Delta ◽  
Reservoir Characterization ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Root Mean Square Amplitude ◽  
Phase Gradient ◽  
Major Fault ◽  
Seismic Sections ◽  
3D Seismic Data

Seismic attributes were evaluated over Edi field, offshore Western Niger Delta, Nigeria, via 3D seismic data. Manual mappings of the horizons and faults on the in-lines and cross-lines of the seismic sections were done. Various attributes were calculated and out put on four horizons corresponding to the well markers at different formations within the well were identified. The four horizons identified, which includes: H1, H2, H3 and H4 were mapped and interpreted across the field. The operational agenda was thru picking given faults segments on the in–line of seismic volume. A total of five faults coded as F1, F2, F3, F4 and F5, F1 and F5 were the major fault and were observed as extending through the field. Structural and horizon mappings were used to generate time structure maps. The maps showed the various positions and orientations of the faults. Different attributes which include: root mean square amplitude, instantaneous phase, gradient magnitude and chaos were run on the 3D seismic data. The amplitude and incline magnitude maps indicate direct hydrocarbon on the horizon maps; this is very important in the drilling of wells because it shows areas where hydrocarbons are present in the subsurface. The seismic attributes revealed information, which was not readily apparent in the raw seismic data.   

Reliability analysis of seismic attribute in the detection of fault-karst

2020 ◽  
Vol 8 (4) ◽  
pp. SP61-SP70
Author(s):  
Yan Ding ◽  
Qizhen Du ◽  
Liyun Fu ◽  
Shikai Jian
Keyword(s):  
Reliability Analysis ◽  
Seismic Data ◽  
Velocity Model ◽  
Seismic Attributes ◽  
Fracture Density ◽  
Seismic Attribute ◽  
Practical Applications ◽  
Fracture Orientation ◽  
Similarity Estimation ◽  
Phase Variance

In the Tarim Basin, various irregular fractured-vuggy reservoirs have developed along with the main faults. These reservoirs are geologically defined as carbonate fault karst. In the past few years, seismic attributes have been widely used for the identification and evaluation of fault karst. However, there has been less reliability analysis regarding their usage. Imaging using the theoretical fault-karst velocity model can reflect the shapes and distributions of fractures and vugs, whereas imaging using the background velocity can simulate seismic data in real cases. We have adopted an approach based on typical fault-karst theoretical forward modeling to evaluate the reliability of seismic attributes in practical applications. First, we extract various attributes from the images using the theoretical velocity and the background velocity using similarity estimation between them to optimize the sensitive attributes. The analysis result indicates that the instantaneous phase, variance, amplitude gradient, coherence, and texture entropy are more suitable to characterize the anomalies of fractures and vugs with prediction accuracy of 71.7%. Because fracture orientation and density are the key parameters for quantifying the differences between the two images, taking coherence as an example, we extract the fracture traces through circular scanlines and circular windows based on the optimized attributes. The coincidence rate between the predicted fracture density and the known model reaches 83%, and that between the predicted fracture orientation and the known model is greater than 95%. With this remarkable coincidence, we can conclude that optimized seismic attributes are reliable for characterizing fractured-vuggy reservoirs.

Geophysical Aspects of Reservoir Characterization of Tight Gas Play in the Dnieper-Donets Basin

2021 ◽  
Author(s):  
Rustem Valiakhmetov ◽  
Andrea Murineddu ◽  
Murat Zhiyenkulov ◽  
Viktor Maliar ◽  
Viktor Bugriy ◽  
...  
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Seismic Attributes ◽  
Static Model ◽  
Donets Basin ◽  
Tight Gas ◽  
Seismic Data Processing ◽  
Exploration Well

Abstract The objective of this work is to describe a comprehensive approach integrating seismic data processing and sets of wireline logs for reservoir characterization of one of the tight gas plays of the Dnieper-Donets basin. This paper intends to discuss a case study from seismic data processing, integrating seismic attributes with formation properties from logs in a geocellular model for sweet spot selection and risk analysis. The workflow during the project included the following steps.Seismic data 3D processing, including 5D interpolation and PSTM migration.Interpretation of limited log data from 4 exploration and appraisal wells.Seismic interpretation and inversion.Building a static model of the field.Recommendations for drilling locations.Evaluation of the drilled well to verify input parameters of the initial model. The static model integrated all available subsurface data and used inverted seismic attributes calibrated to the available logs to constrain the property modelling. Then various deterministic and stochastic approaches were used for facies modeling and estimation of gas-in-place volume. Integrating all the available data provides insights for better understating the reservoir distribution and provided recommendations for drilling locations. Based on the combination of the geocellular model, seismic attributes and seismic inversion results, the operator drilled an exploration well. The modern set of petrophysical logs acquired in the recently drilled well enforced prior knowledge and delivered a robust picture of the tight gas reservoir. The results from the drilled well matched predicted formation properties very closely, which added confidence in the technical approach applied in this study and similar studies that followed later. It is the fork in the road moment for the Dnieper-Donetsk basin with huge tight gas potential in the region that inspires for exploration of other prospects and plays. A synergy of analytical methods with a combination of seismic processing, geomodeling, and reservoir characterization approaches allowed accurate selection of the drilling targets with minimum risk of "dry hole" that has been vindicated by successful drilling outcome in a new exploration well.

Estimation of effective porosity using geostatistics and multiattribute transforms: A case study

Geophysics ◽  
2004 ◽  
Vol 69 (2) ◽  
pp. 352-372 ◽  
Author(s):  
A. G. Pramanik ◽  
V. Singh ◽  
Rajiv Vig ◽  
A. K. Srivastava ◽  
D. N. Tiwary
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Reservoir Characterization ◽  
Middle Eocene ◽  
Seismic Attributes ◽  
Effective Porosity ◽  
3D Seismic ◽  
Porosity Distribution ◽  
Porosity Logs ◽  
3D Seismic Data

The middle Eocene Kalol Formation in the north Cambay Basin of India is producing hydrocarbons in commercial quantity from a series of thin clastic reservoirs. These reservoirs are sandwiched between coal and shale layers, and are discrete in nature. The Kalol Formation has been divided into eleven units (K‐I to K‐XI) from top to bottom. Multipay sands of the K‐IX unit 2–8 m thick are the main hydrocarbon producers in the study area. Apart from their discrete nature, these sands exhibit lithological variation, which affects the porosity distribution. Low‐porosity zones are found devoid of hydrocarbons. In the available 3D seismic data, these sands are not resolved and generate a composite detectable seismic response, making reservoir characterization through seismic attributes impossible. After proper well‐to‐seismic tie, the major stratigraphic markers were tracked in the 3D seismic data volume for structural mapping and carrying out attribute analysis. The 3D seismic volume was inverted to obtain an acoustic impedance volume using a model‐based inversion algorithm, improving the vertical resolution and resolving the K‐IX pay sands. For better reservoir characterization, effective porosity distribution was estimated through different available techniques taking the K‐IX upper sand as an example. Various sample‐based seismic attributes, the impedance volume, and effective porosity logs were used as inputs for this purpose. These techniques are map‐based geostatistical methods using the acoustic impedance volume, stepwise multilinear regression, probabilistic neural networks (PNN) using multiattribute transforms, and a new technique that incorporates both geostatistics and multiattribute transforms (either linear or nonlinear). This paper is an attempt to compare different available techniques for porosity estimation. On comparison, it is found that the PNN‐based approach using ten sample‐based attributes showed highest crosscorrelation (0.9508) between actual and predicted effective porosity logs at eight wells in the study area. After validation, the predicted effective porosity maps for the K‐IX upper sand are generated using different techniques, and a comparison among them is made. The predicted effective porosity map obtained from PNN‐based model provides more meaningful information about the K‐IX upper sand reservoir. In order to give priority to the actual effective porosity values at wells, the predicted effective porosity map obtained from PNN‐based model for the K‐IX upper sand was combined with actual effective porosity values using co‐kriging geostatistical technique. This final map provides geologically more realistic predicted effective porosity distribution and helps in understanding the subsurface image. The implication of this work in exploration and development of hydrocarbons in the study area is discussed.

Sensitivity of 3D 3C synthetic seismograms to anisotropic attenuation and velocity in reservoir models

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. T79-T95 ◽  
Author(s):  
Peng Guo ◽  
George A. McMechan
Keyword(s):  
Fluid Flow ◽  
Aspect Ratio ◽  
Reservoir Characterization ◽  
Fractured Reservoirs ◽  
Staggered Grid ◽  
Fracture Density ◽  
Reservoir Properties ◽  
High Fracture ◽  
Frequency Dependent ◽  
T Matrix

Anisotropic attenuation in fluid-saturated reservoirs with high fracture density may be diagnostic for reservoir characterization. Wave-induced mesoscale fluid flow is considered to be the major cause of intrinsic attenuation at exploration seismic frequencies. We perform tests of the sensitivity, of anisotropic attenuation and velocity, to reservoir properties in fractured HTI media based on the mesoscale fluid flow attenuation mechanism. The viscoelastic T-matrix, a unified effective medium theory of global and local fluid flow mechanisms, is used to compute frequency-dependent anisotropic attenuation and velocity for ranges of reservoir properties, including fracture density, orientation, fracture aspect ratio, fluid type, and permeability. The 3D 3C staggered-grid finite-difference anisotropic viscoelastic modeling with a Crank-Nicolson scheme is used to generate seismograms using the frequency-dependent velocity and attenuation computed by the viscoelastic T-matrix. A standard linear solid model relates the stress and strain relaxation times to the frequency-dependent attenuation, in the relaxation mechanism equation. The seismic signatures resulting from changing viscoelastic reservoir properties are easily visible. Velocity becomes more sensitive to the fracture aspect ratio when considering fluid flow compared with when the fluid is isolated. Anisotropy of attenuation affects 3C viscoelastic seismic data more strongly than velocity anisotropy does. Analysis of the influence of reservoir properties, on seismic properties in mesoscale fluid-saturated fractured reservoirs with high fracture density, suggests that anisotropic attenuation is a potential tool for reservoir characterization.

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