Compaction-induced anisotropy and time-lapse AVO analysis

2015 ◽  
Vol 3 (2) ◽  
pp. SP21-SP33 ◽  
Author(s):  
Nayyer Islam ◽  
Wayne D. Pennington
Keyword(s):  
Elastic Moduli ◽  
Rock Physics ◽  
Time Lapse ◽  
Pressure Effects ◽  
Reservoir Pressure ◽  
Pressure Sensitivity ◽  
Induced Anisotropy ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Sandstone Reservoir

Hydrocarbon reservoirs are often monitored using repeated seismic observations to track fluid movement and other changes. Here, we present a study of compaction-induced anisotropy in an unconsolidated overpressured sandstone reservoir from Teal South field in the Gulf of Mexico. Previous work at Teal South had demonstrated that the time-lapse observations could not be satisfied through models of fluid changes without strong pressure effects acting on the formation rock framework. However, those studies are not highly quantitative, and some minor inconsistencies appear on closer examination. We have examined the effect of the pressure-sensitivity of elastic moduli in the formation and carefully examined the offset-dependence of amplitudes in light of several rock-physics models, empirical and theoretical. The amplitude-variation-with-offset behavior for the interface between overlying shale and the hydrocarbon sand is best modeled under the assumption that this overpressured reservoir becomes anisotropic because it undergoes compaction during production, which reduces the reservoir pressure from highly overpressured to nearly normal for this depth. Although the results obtained here are only weakly constrained due to the limited offset ranges and low fold, this strongly suggests that anisotropic effects in poorly consolidated overpressured reservoirs undergoing primary depletion may in fact dominate over fluid effects after the bubble point has been reached.

ROCK PHYSICS—APPLICATION TO GEOLOGICAL STORAGE OF CO2

2003 ◽  
Vol 43 (1) ◽  
pp. 567 ◽  
Author(s):  
J.J. McKenna ◽  
B. Gurevich ◽  
M. Urosevic ◽  
B.J. Evans
Keyword(s):  
Elastic Moduli ◽  
Co2 Storage ◽  
Rock Physics ◽  
Sedimentary Basins ◽  
Time Lapse ◽  
Seismic Monitoring ◽  
Potential Contribution ◽  
Underground Brine ◽  
Shear Moduli ◽  
Borehole Seismic

Sequestration of anthropogenic CO2 into underground brine-saturated reservoirs is an immediate option for Australia to reduce CO2 emissions into the atmosphere. Many sites for CO2 storage have been defined within many Australian sedimentary basins. It is anticipated that seismic technology will form the foundation for monitoring CO2 storage within the subsurface, although it is recognised that several other technologies will also be used in support of seismic or in situations where seismic recording is not suitable. The success of seismic monitoring will be determined by the magnitude of the change in the elastic properties of the reservoir during the lifecycle of CO2 storage. In the short-term, there will be a strong contrast in density and compressibility between free CO2 and brine. The contrast between these fluids is greater at shallower depth and higher temperature where CO2 resembles a vapour. The significant change in the elastic moduli of the reservoir will enable time-lapse seismic methods to readily monitor structural or hydrodynamic trapping of CO2 below an impermeable seal. Because the acoustic contrast between brine saturated with CO2 and brine containing no dissolved CO2 is very slight, however, dissolved CO2 is unlikely to be detected by any seismic technology, including high-resolution borehole seismic. The detection of increases in porosity, associated with dissolution of susceptible minerals within the reservoir may provide a means for qualitative monitoring of CO2 dissolution. Conversion of aqueous CO2 into carbonate minerals should cause a detectable rise in the elastic moduli of the rock frame, especially the shear moduli. The magnitude of this rise increases with depth and demonstrates the potential contribution that can be made from repeated shear-wave and multi-component seismic measurements. Forward modelling suggests that the optimal reservoir depth for seismic monitoring of CO2 storage within an unconsolidated reservoir is between 1,000 and 2,500 m. Higher reservoir temperature is also preferred so that free CO2 will resemble a vapour.

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.

Influencing factor analysis of the elastic properties of shale with rock-physical model including pressure effects

2020 ◽  
Vol 8 (3) ◽  
pp. T515-T524
Author(s):  
Zhaoyun Zong ◽  
Man Jiang ◽  
Miaomiao Xu
Keyword(s):  
Elastic Moduli ◽  
Pore Space ◽  
Influencing Factor ◽  
Rock Physics ◽  
Critical Value ◽  
Pressure Effects ◽  
Petroleum Exploration ◽  
Solid Matrix ◽  
Effective Pressure ◽  
Shale Reservoirs

With the continuous petroleum exploration around the world, the target of exploration is converting from conventional to deep, unconventional reservoirs. The pressure condition on those new target layers is different from the conventional reservoir, and pressure is one of the important factors affecting the elastic moduli and velocities of shale reservoirs. Therefore, it is necessary to take pressure effects into consideration in rock-physics modeling. We initially adopted a novel iterative rock-physical modeling approach on the basis of pore space stiffness theory to analyze pressure’s influence on shale. Pore space stiffness theory assumes that pores own their own stiffness like the solid matrix of rocks, which is related to the effective pressure. We have implemented plenty of numerical analysis on the effect of pressure on shale and found out the most contributive factor to the moduli and velocities of shale. Our result indicates that when the effective pressure is smaller than the critical value, the elastic moduli and elastic wave velocities of shale increase significantly with the increase of effective pressure. The elastic moduli and velocities tend to be constant when the effective pressure goes beyond that critical value. By comparison, we found that the most contributive mineral in shale is clay, and the porosity has the greatest effect on elastic moduli and velocities when the mineral composition of shale stays unchanged. The influence of pressure is not as obvious as other factors in shale reservoirs with low porosity (lower than 10%) because pores occupy a relatively small percentage of the total volume.

Three-term amplitude-variation-with-offset projections

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. N51-N65 ◽  
Author(s):  
Vaughn Ball ◽  
Luis Tenorio ◽  
Christian Schiøtt ◽  
Michelle Thomas ◽  
J. P. Blangy
Keyword(s):  
Rock Physics ◽  
Projection Methods ◽  
Well Logs ◽  
Rock Properties ◽  
Inversion Method ◽  
Practical Implementation ◽  
Angle Of Incidence ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Maximum Angle

A three-term (3T) amplitude-variation-with-offset projection is a weighted sum of three elastic reflectivities. Parameterization of the weighting coefficients requires two angle parameters, which we denote by the pair [Formula: see text]. Visualization of this pair is accomplished using a globe-like cartographic representation, in which longitude is [Formula: see text], and latitude is [Formula: see text]. Although the formal extension of existing two-term (2T) projection methods to 3T methods is trivial, practical implementation requires a more comprehensive inversion framework than is required in 2T projections. We distinguish between projections of true elastic reflectivities computed from well logs and reflectivities estimated from seismic data. When elastic reflectivities are computed from well logs, their projection relationships are straightforward, and they are given in a form that depends only on elastic properties. In contrast, projection relationships between reflectivities estimated from seismic may also depend on the maximum angle of incidence and the specific reflectivity inversion method used. Such complications related to projections of seismic-estimated elastic reflectivities are systematized in a 3T projection framework by choosing an unbiased reflectivity triplet as the projection basis. Other biased inversion estimates are then given exactly as 3T projections of the unbiased basis. The 3T projections of elastic reflectivities are connected to Bayesian inversion of other subsurface properties through the statistical notion of Bayesian sufficiency. The triplet of basis reflectivities is computed so that it is Bayes sufficient for all rock properties in the hierarchical seismic rock-physics model; that is, the projection basis contains all information about rock properties that is contained in the original seismic.

scholarly journals AVO as a fluid indicator: A physical modeling study

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. C9-C17 ◽  
Author(s):  
Aaron Wandler ◽  
Brian Evans ◽  
Curtis Link
Keyword(s):  
Physical Model ◽  
Physical Modeling ◽  
Model Experiment ◽  
Close Agreement ◽  
Time Lapse ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Zoeppritz Equations ◽  
Seismic Amplitude ◽  
Gradient Domain

Information on time-lapse changes in seismic amplitude variation with offset (AVO) from a reservoir can be used to optimize production. We designed a scaled physical model experiment to study the AVO response of mixtures of brine, oil, and carbon dioxide at pressures of 0, 1.03, and [Formula: see text]. The small changes in density and velocity for each fluid because of increasing pressure were not detectable and were assumed to lie within the error of the experiment. However, AVO analysis was able to detect changes in the elastic properties between fluids that contained oil and those that did not. When the AVO response was plotted in the AVO intercept-gradient domain, fluids containing oil were clearly separated from fluids not containing oil. This was observed in the AVO response from both the top and base of the fluids in the physical model. We then compared the measured AVO response with the theoretical AVO response given by the Zoeppritz equations. The measured and theoretical AVO intercept responses for the top fluid reflection agree well, although the AVO gradients disagree slightly. For the fluid base reflection, the measured and theoretical responses are in close agreement.

Seismic reservoir characterization of a class-1 amplitude variation with offset turbiditic system located offshore Cote d’Ivoire, West Africa

2018 ◽  
Vol 6 (2) ◽  
pp. SD115-SD128
Author(s):  
Pedro Alvarez ◽  
William Marin ◽  
Juan Berrizbeitia ◽  
Paola Newton ◽  
Michael Barrett ◽  
...  
Keyword(s):  
West Africa ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Rock Properties ◽  
Well Log ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Fluid Content ◽  
Class 1

We have evaluated a case study, in which a class-1 amplitude variation with offset (AVO) turbiditic system located offshore Cote d’Ivoire, West Africa, is characterized in terms of rock properties (lithology, porosity, and fluid content) and stratigraphic elements using well-log and prestack seismic data. The methodology applied involves (1) the conditioning and modeling of well-log data to several plausible geologic scenarios at the prospect location, (2) the conditioning and inversion of prestack seismic data for P- and S-wave impedance estimation, and (3) the quantitative estimation of rock property volumes and their geologic interpretation. The approaches used for the quantitative interpretation of these rock properties were the multiattribute rotation scheme for lithology and porosity characterization and a Bayesian lithofluid facies classification (statistical rock physics) for a probabilistic evaluation of fluid content. The result indicates how the application and integration of these different AVO- and rock-physics-based reservoir characterization workflows help us to understand key geologic stratigraphic elements of the architecture of the turbidite system and its static petrophysical characteristics (e.g., lithology, porosity, and net sand thickness). Furthermore, we found out how to quantify and interpret the risk related to the probability of finding hydrocarbon in a class-1 AVO setting using seismically derived elastic attributes, which are characterized by having a small level of sensitivity to changes in fluid saturation.

Introduction to this special section: Rock physics

2021 ◽  
Vol 40 (9) ◽  
pp. 644-644
Author(s):  
Agnibha Das ◽  
Madhumita Sengupta
Keyword(s):  
Risk Mitigation ◽  
Special Section ◽  
Rock Physics ◽  
Time Lapse ◽  
Reservoir Properties ◽  
Amplitude Variation With Offset ◽  
Digital Rock Physics ◽  
Exploration Risk ◽  
Distributed Acoustic Sensing ◽  
And Inversion

In simple terms, rock physics provides the much-needed link between measurable elastic properties of rocks and their intrinsic properties. This enables us to connect seismic data, well logs, and laboratory measurements to minerology, porosity, permeability, fluid saturations, and stress. Rock-physics relationships/models are used to understand seismic signatures in terms of reservoir properties that help in exploration risk mitigation. Traditionally, rock physics has played an irreplaceable role in amplitude variation with offset (AVO) modeling and inversion, 3D/4D close-the-loop studies, and seismic time-lapse analysis and interpretation. Today, rock-physics research and application have influenced a much wider space that spans digital rock physics, microseismic, and distributed acoustic sensing (DAS) data analysis. In this special section, we have included papers that cover much of these advanced methods, providing us with a better understanding of subsurface elastic and transport properties, thereby reducing bias and uncertainties in quantitative interpretation.

Sign in / Sign up

Export Citation Format

Share Document