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Results
Abstract Compaction effects can obscure the impedance separation between hydrocarbon-bearing and fully brine-saturated sandstones. We have improved their discrimination by removing depth-related trends from inverted seismic impedance. Although the ratio of compressional- to shear-wave velocity versus seismic compressional-wave impedance crossplots shows differences among pay, brine sand, and shale trends, using absolute inverted impedances only imperfectly distinguishes hydrocarbon sands from brine sands due to outliers. In a given locality, statistical comparison of well log and seismic-derived impedances enables us to obtain a shale impedance model for a lithology baseline to detrend the impedance from the effects of burial and overburden. This has the effect of unmasking anomalies associated with hydrocarbon-bearing sands and serves as a reliable fluid discriminator. For an offshore Gulf of Mexico data set on the flank of a salt dome, with pay occurring over a wide range of depths, we identify hydrocarbon-bearing sands with a greater success rate after detrending the absolute seismic impedance.
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.87)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.71)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.70)
P-to-S-wave velocity ratio in organic shales
Omovie, Sheyore John (Oxy) | Castagna, John P. (University of Houston)
ABSTRACT In situ P- and S-wave velocity measurements in a variety of organic-rich shales exhibit P-to-S-wave velocity ratios that are significantly lower than lithologically similar fully brine-saturated shales having low organic content. It has been hypothesized that this drop could be explained by the direct influence of kerogen on the rock frame and/or by the presence of free hydrocarbons in the pore space. The correlation of hydrocarbon saturation with total organic content in situ makes it difficult to separate these possible mechanisms using log data alone. Theoretical bounding equations, using pure kerogen as an end-member component without associated gas, indicate that kerogen reduces the P- and S-wave velocities but does not in general reduce their ratio enough to explain the observed low velocity ratio. The theoretical modeling is consistent with ultrasonic measurements on organic shale core samples that indicate no dependence of velocity ratios on the kerogen volume alone. Sonic log measurements of P- and S-wave velocities in seven organic-rich shale formations deviate significantly (typically more than 5%) from the Greenberg-Castagna empirical brine-saturated shale trend toward lower velocity ratios. In these formations, and on core measurements, Gassmann fluid substitution to 100% brine saturation yields velocity ratios consistent with the Greenberg-Castagna velocity trend for fully brine-saturated shales, despite the high organic content. These sonic and ultrasonic measurements, as well as theoretical modeling, suggest that the velocity ratio reduction in organic shales is best explained by the presence of free hydrocarbons.
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (1.00)
- Geophysics > Borehole Geophysics (1.00)
- North America > United States > West Virginia > Appalachian Basin > Marcellus Shale Formation (0.99)
- North America > United States > Virginia > Appalachian Basin > Marcellus Shale Formation (0.99)
- North America > United States > Texas > West Gulf Coast Tertiary Basin > Eagle Ford Shale Formation (0.99)
- (48 more...)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale oil (1.00)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- (3 more...)
Abstract Using time-frequency and time-phase analysis we found that for an isolated thin bed in a binary-impedance setting, there is no observable sensitivity in preferential illumination as layered net-to-gross (NTG) changes within the isolated thin bed, regardless of the way the internal layering is distributed โ either uniformly or semirandomly. The NTG signature is observed on the amplitude (magnitude) responses, rather than any specific frequency or phase component. On the other hand, external mutual thin-bed interference can significantly change the preferred phase component for each participating target. This phenomenon is largely driven by the embedded seismic wavelet that determines the nominal seismic response of an isolated thin layer and what phase component would preferentially illuminate it. For vertical separations between mutually interfering and elastically comparable thin beds in which mutual constructive interference is achieved, the target bed will be preferentially illuminated at a phase component that is very close to that of a total seismic isolation, whereas the occurrence of mutual destructive interference will cause a significant departure on the phase preferential illumination from that of an isolated seismic thin bed. All these observations can provide an avenue to yield more robust stratigraphic interpretations of seismic data and enhance the confidence on subsurface description.
- South America > Venezuela (0.68)
- North America > United States > Texas (0.29)
- Geology > Geological Subdiscipline > Stratigraphy (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.48)
Abstract In the Abu Madi Formation of the Nile Delta Basin, false bright spots may be misinterpreted as being indicative of hydrocarbons due to mixed clastics and carbonates. However, rock-physics analysis of well logs in a particular prospect area where such ambiguity exists suggests that attributes derived using extended elastic impedance (EEI) inversion may help identify hydrocarbons because they better show anomalous behavior in particular directions that are readily related to pore fluids and lithology. The EEI attributes calculated from well logs correlate extremely well to lithology and fluid properties, thereby differentiating amplitude anomalies caused by gas-bearing sandstones encased in shale from similar amplitudes caused by juxtaposition of high-impedance carbonates over lower impedance water-filled sandstones. Comparing seismically derived EEI attributes to well logs from a productive well and a nonproductive well indicates that seismic inversion can successfully identify lithologies such as shales, sandstones, carbonates, and anhydrite and distinguish gas-bearing from water-bearing sandstones. The technique can thus potentially be used to better delineate and risk prospects in the area, as well as assisting exploration efforts in other locations where similar ambiguities in amplitude interpretation exist.
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.48)
- Asia > Middle East > Israel > Southern District > Eastern Mediterranean Basin (0.99)
- Africa > Middle East > Egypt > Nile Delta > Nile Delta Basin > Sequoia Field (0.99)
- Africa > Middle East > Egypt > Nile Delta > Nile Delta Basin > Abu Madi Formation (0.99)
- Africa > Middle East > Egypt > Mediterranean Sea > Nile Delta Basin > Saffron Field (0.98)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Stochastic Rock Physics Inversion
Cobos, Carlos Manuel (Repsol Services) | Castagna, John P. (U. of Houston)
Abstract The purpose of this paper is to introduce a stochastic seismic inversion algorithm based on Markov Chain Monte Carlo Simulation. The suggested inversion scheme generates a set of possible combinations of rock properties that can explain seismic amplitude responses in terms of lithology, pore structure and fluid variations. The result of the probabilistic seismic inversion is a seismic lithofacies catalog than can describe the elastic response of the studied subsurface interval. The main advantage of this technique is that the results consist of multiple equally probable rock properties models as an alternative to multiple elastic properties scenarios. Therefore, no post facto elastic to rock properties conversion is needed. The method might be used either in exploratory areas or hydrocarbon field development. In exploratory areas, the stochastic rock physics inversion can support the evaluation for hydrocarbon potential considering the effects of reservoir properties on seismic signatures for different geologic scenarios and physical conditions, with the prime goal of minimizing uncertainties and risk. In field development areas, stochastic seismic inversion produces multiple equally probable rock properties models that can explain the real 3D seismic response and can be used to constrain possible reservoir models used for hydrocarbon reserve estimation and reservoir production simulation. The probabilistic inversion algorithm was tested on a synthetic model that is based on real well log data. The objective of the synthetic test is to demonstrate the feasibility of the estimation of critical rock properties for hydrocarbon exploration, such as total porosity and reservoir fraction. The synthetic test results confirmed the capability of the proposed inversion technique to accurately predict the rock properties of the reservoir seismic lithofacies, even for seismically thin layers. Introduction Conventional seismic reservoir characterization (SRC) techniques were developed more than forty years ago for exploration plays where the hydrocarbon's seismic responses were relatively easy to identify. Early reservoir characterization workflows were usualy based on direct hydrocarbon indicator (DHI) identification techniques centered on post stack seismic amplitude analysis and AVO inversion. DHIs plays are usually related to shallow high porosity reservoirs with significantly lower acoustic impedance than the surrounding rocks. The associated seismic signatures of these hydrocarbon filled high porosity reservoirs can be anomalous high amplitude reflections called "bright spots". Nowadays, conventional seismic reservoir characterization techniques are becoming obsolete, since the oil industry is moving to explore areas were the hydrocarbons are located in deeper and more complex reservoirs. These new hydrocarbon plays are characterized by low porosity and low permeability reservoirs with near to undetectable pore fluid response. It means that the future seismic reservoir caracterization goal is to predict rock properties such as porosity, lithology and rock fabric of compacted and cemented porous rock. The second more important SRC challenge is to improve the seismic vertical resolution. Currently, seismic inversion resolution is still low for the new exploration/development challenges and improvement of seismic derived elastic parameters is paramount for the application of reservoir properties prediction. Techniques such as stochastic inversion have been initially developed in an attempt to obtain from seismic data quantitative information about subsurface rock properties on a very detailed scale. The goal of this paper is to introduce an inversion technique based on Markov Chain Monte Carlo simulation that can be implemented in a stochastic petrophysical inversion scheme. The stochastic seismic inversion's objective is to produce a set of equiprobable rock properties volumes that can describe the elastic seismic response of the studied interval and their associated uncertainties. The main advantage of this petrophysical inversion technique is that the results are multiple equally probable rock properties models instead of multiple elastic properties scenarios. Therefore, no elastic to rock properties conversion is needed after the inversion is performed. The method might be used either in exploratory or development areas.
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.33)
Physical properties of shallow-water flow (SWF) sands differ from most reservoir and seal rocks studied for petroleum purposes. These materials exist near the transition zone between rocks and sediments. Our investigations, the subject of this article, suggest that physical properties of SWF sands are amenable to a prediction methodology that uses high-resolution multicomponent seismic data.
- Geology > Geological Subdiscipline > Geomechanics (0.97)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.49)
Amplitude variation with offset AVO interpretation may be facilitated by crossplotting the AVO intercept A and gradient B. Under a variety of reasonable petrophysical assumptions, brinesaturated sandstones and shales follow a welldefined background trend in the A-B plane. Generally, A and B are negatively correlated for background rocks, but they may be positively correlated at very high ratios, such as may occur in very soft shallow sediments. Thus, even fully brinesaturated shallow events with large reflection coefficients may exhibit large increases in AVO. Deviations from the background trend may be indicative of hydrocarbons or lithologies with anomalous elastic properties. However, in contrast to the common assumptions that gassand amplitude increases with offset, or that the reflection coefficient becomes more negative with increasing offset, gas sands may exhibit a variety of AVO behaviors. A classification of gas sands based on location in the A-B plane, rather than on normalincidence reflection coefficient, is proposed. According to this classification, brightspot gas sands fall in quadrant III and have negative AVO intercept and gradient. These sands exhibit the amplitude increase versus offset which has commonly been used as a gas indicator. Highimpedance gas sands fall in quadrant IV and have positive AVO intercept and negative gradient. Consequently, these sands initially exhibit decreasing AVO and may reverse polarity. These behaviors have been previously reported and are addressed adequately by existing classification schemes. However, quadrant II gas sands have negative intercept and positive gradient. Certain classical bright spots fall in quadrant II and exhibit decreasing AVO. Examples show that this may occur when the gassand shearwave velocity is lower than that of the overlying formation. Common AVO analysis methods such as partial stacks and product AB indicators are complicated by this nonuniform gassand behavior and require prior knowledge of the expected gassand AVO response. However, Smith and Gidlows 1987 fluid factor, and related indicators, will theoretically work for gas sands in any quadrant of the A-B plane.
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.37)
A worldwide collection of 25 sets of velocity and density measurements from adjacent shales, brine sands, and gas sands was acquired with fullwaveform sonic, dipole sonic, and conventional well logging devices and/or in the laboratory. These data provide theoretical shale over brinesand and shale over gassand Pwave and Swave normalincedence reflection coefficents and , AVO intercepts A, AVO gradients B, the AVO indicators reflection coefficient difference, and A B AVO product. The reflection coefficient difference is found to be a more universal indicator than the AVO product in clastic stratigraphic intervals. For shale over brinesand reflections, the average tends to be near zero and relatively invariant with depth. Irrespective of gassand impedance, is always negative for shale over reservoir quality gassand reflections and more negative than for the corresponding brinesand reflections. In comparison, the AVO product may be positive, near zero, or negative for gassands depending on the impedance contrast with the overlying shale. These measurements also verify that is well approximated by a simple linear combination of A and B.
The seismic literature defines two distinct types of anisotropy: Eastwood, R. L., and Castagna, J. P.. 1983.
- Geology > Mineral > Silicate (0.72)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.56)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (1.00)
- Geophysics > Borehole Geophysics (1.00)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- North America > United States > New Mexico > Permian Basin > Wolfcamp Formation (0.99)