Derisking low-saturation gas in Tertiary turbidite reservoirs

2016 ◽  
Vol 4 (3) ◽  
pp. SN31-SN43
Author(s):  
Krzysztof M. Wojcik ◽  
Ezequiel Gonzalez ◽  
Robert E. Vines
Keyword(s):  
Geophysical Methods ◽  
False Positives ◽  
Bayesian Probability ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Seal Integrity ◽  
Residual Gas ◽  
Net To Gross ◽  
High Possibility ◽  
Proper Context

Occurrences of low-saturation gas (LSG) in tertiary turbidite reservoirs are common and often characterized by anomalous amplitude/amplitude variation with offset (AVO) response, which can be classified as false positives. LSG cases are difficult to derisk with geophysical methods because the anomalous responses may be very similar to success-case (oil or gas) anomalies. LSG failures may represent true residual gas in cases of seal integrity failure (“blown” trap) or variable saturation of gas in low net-to-gross laminated sandstone/siltstone or siltstone/mudstone intervals (“generic LSG”), which represent a type of reservoir failure. Derisking exploration opportunities burdened with a high possibility of LSG failure require an integrated evaluation of the geophysical evidence in the proper context of charge setting, reservoir/seal stratigraphy, structural setting, and trap geometry. Although geophysical methods may not provide fully conclusive predictions, the integration of geophysical observations with a geologic framework and realistic geologic chance factors can result in effective derisking of potential low-saturation failure cases through the estimation of geophysical scenario likelihood values and Bayesian probability updates.

Fracture mapping using seismic amplitude variation with offset and azimuth analysis at the Weyburn CO2 storage site

Geophysics ◽  
2012 ◽  
Vol 77 (6) ◽  
pp. B295-B306 ◽  
Author(s):  
Alexander Duxbury ◽  
Don White ◽  
Claire Samson ◽  
Stephen A. Hall ◽  
James Wookey ◽  
...  
Keyword(s):  
Cross Sections ◽  
Co2 Storage ◽  
Horizontal Stress ◽  
Storage Site ◽  
Fracture Zones ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Seal Integrity ◽  
Cap Rock ◽  
Weyburn Field

Cap rock integrity is an essential characteristic of any reservoir to be used for long-term [Formula: see text] storage. Seismic AVOA (amplitude variation with offset and azimuth) techniques have been applied to map HTI anisotropy near the cap rock of the Weyburn field in southeast Saskatchewan, Canada, with the purpose of identifying potential fracture zones that may compromise seal integrity. This analysis, supported by modeling, observes the top of the regional seal (Watrous Formation) to have low levels of HTI anisotropy, whereas the reservoir cap rock (composite Midale Evaporite and Ratcliffe Beds) contains isolated areas of high intensity anisotropy, which may be fracture-related. Properties of the fracture fill and hydraulic conductivity within the inferred fracture zones are not constrained using this technique. The predominant orientations of the observed anisotropy are parallel and normal to the direction of maximum horizontal stress (northeast–southwest) and agree closely with previous fracture studies on core samples from the reservoir. Anisotropy anomalies are observed to correlate spatially with salt dissolution structures in the cap rock and overlying horizons as interpreted from 3D seismic cross sections.

Deepwater reservoir heterogeneity delineation using rock physics and extended elastic impedance inversion: Nile Delta case study

2014 ◽  
Vol 2 (4) ◽  
pp. T205-T219 ◽  
Author(s):  
Ahmed Hafez ◽  
Folkert Majoor ◽  
John P. Castagna
Keyword(s):  
Nile Delta ◽  
Rock Physics ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Impedance Inversion ◽  
Net To Gross ◽  
Deepwater Channel ◽  
Static Connectivity ◽  
Elastic Impedance

Deepwater channel reservoirs in the Nile Delta are delineated using extended elastic impedance inversion (EEI). We used the following workflow: seismic spectral blueing, rock physics and amplitude variation with offset modeling, seismic EEI and interpretation of the inverted cubes in terms of geologic facies, net-to-gross ratio, and static connectivity among depositional geobodies. Three subenvironments within the targeted reservoir interval were recognized using a combination of shale volume and [Formula: see text]-inverted cubes. These were used to generate 3D geobodies and a net-pay thickness map that were used in turn to calculate reservoir volumetrics. The results from the workflow matched well logs and could thus be used to investigate the potential of nearby prospects that have the same geologic settings.

The impact of reservoir scale on amplitude variation with offset

2016 ◽  
Vol 65 (3) ◽  
pp. 736-746 ◽  
Author(s):  
Chao Xu ◽  
Jianxin Wei ◽  
Bangrang Di
Keyword(s):  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
The Impact

Information on elastic parameters obtained from the amplitudes of reflected waves

Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1426-1436 ◽  
Author(s):  
Wojciech Dȩbski ◽  
Albert Tarantola
Keyword(s):  
Mass Density ◽  
Seismic Velocities ◽  
Elastic Parameters ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Reflected Waves ◽  
Seismic Amplitude ◽  
Earth Models ◽  
Definition Of ◽  
Proper Analysis

Seismic amplitude variation with offset data contain information on the elastic parameters of geological layers. As the general solution of the inverse problem consists of a probability over the space of all possible earth models, we look at the probabilities obtained using amplitude variation with offset (AVO) data for different choices of elastic parameters. A proper analysis of the information in the data requires a nontrivial definition of the probability defining the state of total ignorance on different elastic parameters (seismic velocities, Lamé’s parameters, etc.). We conclude that mass density, seismic impedance, and Poisson’s ratio constitute the best resolved parameter set when inverting seismic amplitude variation with offset data.

Model misspecification and bias in the least-squares algorithm: Implications for linearized isotropic AVO

2021 ◽  
Vol 40 (9) ◽  
pp. 646-654
Author(s):  
Henning Hoeber
Keyword(s):  
Least Squares ◽  
Model Misspecification ◽  
Forward Model ◽  
Model Parameters ◽  
Omitted Variables ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Omitted Variable Bias ◽  
Least Squares Fit ◽  
Variable Bias

When inversions use incorrectly specified models, the estimated least-squares model parameters are biased. Their expected values are not the true underlying quantitative parameters being estimated. This means the least-squares model parameters cannot be compared to the equivalent values from forward modeling. In addition, the bias propagates into other quantities, such as elastic reflectivities in amplitude variation with offset (AVO) analysis. I give an outline of the framework to analyze bias, provided by the theory of omitted variable bias (OVB). I use OVB to calculate exactly the bias due to model misspecification in linearized isotropic two-term AVO. The resulting equations can be used to forward model unbiased AVO quantities, using the least-squares fit results, the weights given by OVB analysis, and the omitted variables. I show how uncertainty due to bias propagates into derived quantities, such as the χ-angle and elastic reflectivity expressions. The result can be used to build tables of unique relative rock property relationships for any AVO model, which replace the unbiased, forward-model results.

An integrated broadband preprocessing method for towed-streamer seismic data

Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. V201-V221 ◽  
Author(s):  
Mehdi Aharchaou ◽  
Erik Neumann
Keyword(s):  
Seismic Data ◽  
High Frequency ◽  
Pressure Data ◽  
Amplitude Variation ◽  
Field Source ◽  
Amplitude Variation With Offset ◽  
Ringing Artifacts ◽  
Joint Application ◽  
Amplitude Compensation ◽  
Unified Method

Broadband preprocessing has become widely used for marine towed-streamer seismic data. In the standard workflow, far-field source designature, receiver and source-side deghosting, and redatuming to mean sea level are applied in sequence, with amplitude compensation for background [Formula: see text] delayed until the imaging or postmigration stages. Thus, each step is likely to generate its own artifacts, quality checking can be time-consuming, and broadband data are only obtained late in this chained workflow. We have developed a unified method for broadband preprocessing — called integrated broadband preprocessing (IBP) — which enables the joint application of all the above listed steps early in the processing sequence. The amplitude, phase, and amplitude-variation-with-offset fidelity of IBP are demonstrated on pressure data from the shallow, deep, and slanted streamers. The integration allows greater sparsity to emerge in the representation of seismic data, conferring clear benefits over the sequential application. Moreover, time sparsity, full dimensionality, and early amplitude [Formula: see text] compensation all have an impact on broadband data quality, in terms of reduced ringing artifacts, improved wavelet integrity at large crossline angles, and fewer residual high-frequency multiples.

Meet West Africa deep exploration challenge with geomorphology and targeted amplitude variation with offset inversion

2020 ◽  
Vol 8 (1) ◽  
pp. SA25-SA33
Author(s):  
Ellen Xiaoxia Xu ◽  
Yu Jin ◽  
Sarah Coyle ◽  
Dileep Tiwary ◽  
Henry Posamentier ◽  
...  
Keyword(s):  
West Africa ◽  
Critical Role ◽  
Reservoir Quality ◽  
Quality Prediction ◽  
Reservoir Prediction ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Simultaneous Inversion ◽  
Seismic Amplitude ◽  
Class 1

Seismic amplitude has played a critical role in the exploration and exploitation of hydrocarbon in West Africa. Class 3 and 2 amplitude variation with offset (AVO) was extensively used as a direct hydrocarbon indicator and reservoir prediction tool in Neogene assets. As exploration advanced to deeper targets with class 1 AVO seismic character, the usage of seismic amplitude for reservoir presence and quality prediction became challenged. To overcome this obstacle, (1) we used seismic geomorphology to infer reservoir presence and precisely target geophysical analysis on reservoir prone intervals, (2) we applied rigorous prestack data preparation to ensure the accuracy and precision of AVO simultaneous inversion for reservoir quality prediction, and (3) we used lateral statistic method to sum up AVO behavior in regions of contrasts to infer reservoir quality changes. We have evaluated a case study in which the use of the above three techniques resulted in confident prediction of reservoir presence and quality. Our results reduced the uncertainty around the biggest risk element in reservoir among the source, charge, and trap mechanism in the prospecting area. This work ultimately made a significant contribution toward a confident resource booking.

Signal leakage in f-x deconvolution algorithms

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. W31-W45 ◽  
Author(s):  
Necati Gülünay
Keyword(s):  
Field Data ◽  
New Technologies ◽  
Filter Design ◽  
Synthetic Data ◽  
Data Sets ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Backward Design ◽  
Use Of Data ◽  
Domain Prediction

The old technology [Formula: see text]-[Formula: see text] deconvolution stands for [Formula: see text]-[Formula: see text] domain prediction filtering. Early versions of it are known to create signal leakage during their application. There have been recent papers in geophysical publications comparing [Formula: see text]-[Formula: see text] deconvolution results with the new technologies being proposed. These comparisons will be most effective if the best existing [Formula: see text]-[Formula: see text] deconvolution algorithms are used. This paper describes common [Formula: see text]-[Formula: see text] deconvolution algorithms and studies signal leakage occurring during their application on simple models, which will hopefully provide a benchmark for the readers in choosing [Formula: see text]-[Formula: see text] algorithms for comparison. The [Formula: see text]-[Formula: see text] deconvolution algorithms can be classified by their use of data which lead to transient or transient-free matrices and hence windowed or nonwindowed autocorrelations, respectively. They can also be classified by the direction they are predicting: forward design and apply; forward design and apply followed by backward design and apply; forward design and apply followed by application of a conjugated forward filter in the backward direction; and simultaneously forward and backward design and apply, which is known as noncausal filter design. All of the algorithm types mentioned above are tested, and the results of their analysis are provided in this paper on noise free and noisy synthetic data sets: a single dipping event, a single dipping event with a simple amplitude variation with offset, and three dipping events. Finally, the results of applying the selected algorithms on field data are provided.

Examination of AVO responses in the eastern deepwater Gulf of Mexico

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1864-1876 ◽  
Author(s):  
Tad M. Smith ◽  
Carl H. Sondergeld
Keyword(s):  
Gulf Of Mexico ◽  
Oil And Gas ◽  
Shear Velocity ◽  
Bright Spot ◽  
Velocity Data ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Saturated Sands ◽  
Local Shear

Exploration programs in deepwater Tertiary basins (e.g., the Gulf of Mexico) typically rely on bright‐spot and amplitude variation with offset (AVO) technology to help identify oil‐ and gas‐charged sands. The reliance on these attributes, along with the high cost of exploration programs in deepwater environments, has driven the need to examine the limitations of these technologies and to build robust models for the conditions under which AVO is useful as a fluid and/or lithology indicator. We build subregional AVO background trends for both brine‐ and gas‐saturated sands from several wells from the eastern deepwater Gulf of Mexico. These trends are built from the depth dependencies of velocities and densities for both shale and sands (brine saturated). Simple models of AVO gradient and intercept are constructed as a function of depth below the mud line. Sand and shale properties show little velocity contrast, justifying the interpretation of these data in the context of linearized AVO models. In addition to the in‐situ brine response, the response to gas is also calculated. These trend models indicate that the AVO response is suppressed (although still positive) below a depth of approximately 10 000 ft below the mud line. Even optimistic porosity modeling (sand porosity >30°) does not substantially change this conclusion. An important corollary is that the absence of a strong AVO anomaly at these deeper depths cannot be used with confidence when ruling out hydrocarbon presence. This observation also highlights the need to crossplot attributes to best predict hydrocarbon presence. Velocity data collected as part of this study are also used to generate a local shear velocity estimator for sands and shale. These shear estimators are similar in form to other published estimators, but minor differences in coefficients may become important in AVO modeling.

Linearized amplitude variation with offset (AVO) inversion with supercritical angles

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. E49-E55 ◽  
Author(s):  
Jonathan E. Downton ◽  
Charles Ursenbach
Keyword(s):  
Reflection Coefficient ◽  
Critical Angle ◽  
Waveform Inversion ◽  
Phase Variation ◽  
Reflection Coefficients ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Zoeppritz Equations ◽  
Avo Inversion ◽  
Angle Data

Contrary to popular belief, a linearized approximation of the Zoeppritz equations may be used to estimate the reflection coefficient for angles of incidence up to and beyond the critical angle. These supercritical reflection coefficients are complex, implying a phase variation with offset in addition to amplitude variation with offset (AVO). This linearized approximation is then used as the basis for an AVO waveform inversion. By incorporating this new approximation, wider offset and angle data may be incorporated in the AVO inversion, helping to stabilize the problem and leading to more accurate estimates of reflectivity, including density reflectivity.

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