Xie, Xiang (Bohai Oilfield Research Institute) | Fan, Jianhua (Bohai Oilfield Research Institute) | Zhang, Zhongqiao (Bohai Oilfield Research Institute) | Shen, Hongtao (Bohai Oilfield Research Institute) | Guo, Naichuan (Bohai Oilfield Research Institute)
Forward modeling and AVO analysis on wedge models are integrated in this paper to analyze the influence of thickness of a single thin bed on AVO responses. Study shows that tuning effect similar with post-stack amplitude can also be observed on pre-stack AVO intercept (P) and gradient (G) as well as their product P*G, which all reach their maximum at 1/4 wavelength and then gradually decrease to stable values with the increase of layer thickness. Quantitative analysis is subsequently conducted on AVO tuning effect through detailed comparison of AVO forward modeling on gas and brine saturated wedge models. It’s indicated that the AVO responses of both gas and brine saturated models are obviously strengthened at the tuning thickness without changing the original AVO types, namely the algebraic sign of intercept and gradient. That is to say, the differences of AVO responses between gas and brine saturated thin beds are strengthened due to tuning effect, thus making gas and brine saturated thin beds more distinguishable, which has great significances for fluid identification in thin beds.
Presentation Date: Monday, September 25, 2017
Start Time: 2:40 PM
Location: Exhibit Hall C, E-P Station 3
Presentation Type: EPOSTER
The objective of this work is to use AVO intercept and gradient, in conjunction with well-log petrophysics analysis, to discriminate and classify lithofacies in a shaly sand reservoir. Careful log and core analysis, and rock physics modeling was used to identify the important seismic litho-classes. Monte Carlo AVO simulations based on statistical rock physics were used to set up the class-conditioned probability distributions (pdfs) of intercept and gradient. The effect of thin-layer anisotropy on the probability distributions of AVO intercept and gradient was considered by simulating various realizations of sand-shale thin layers. Monte Carlo simulations, by taking into account distributions of values instead of single average values, help to avoid the flaw of averages (Mukerji and Mavko, 2005). Monte Carlo simulations also give us confidence intervals and other measures of uncertainty. Computations using averages and average trends alone do not give any indication of the uncertainty due to the variability in the properties. The pdfs were then used to classify the seismic AVO intercept and gradient cubes to estimate the most-likely facies and obtain lithofacies probability cubes.
Adjustments can be made to the data so that actual trends conform to the predicted background trends. The result will be a calibrated dataset that results in amplitudes, cross-plots and rock property contrast curves that agree with well data. Examples The example of a seismic data set, calibrated by scaling, as described above, so that the rock property based background relationships are preserved results in the crossplot of a combination of AVO attributes and derived rock properties can be found in Figures 2, 3 and 4. The three types of data; seismic, synthetic and well, agree with each other. These results hold as long as the seismic data is properly calibrated so as to preserve the background rock property relationships and the dynamic range of the data is not corrupted. Conclusions If background rock property relationships are used to calibrate seismic data so that average or background seismic amplitudes agree with synthetics created from well data, at the same location, then the resulting seismic AVO attributes and rock property contrasts will agree quantitatively with the those derived from wells or synthetics. In the case of cross-plots the background trend slopes and the position of a particular anomalous events will agree with cross-plots derived from well or synthetic data cross-plots. An assumption is made that the seismic used in the described calibration does not have processing steps applied that distort the amplitudes and dynamic range of the data. Examples including well, synthetic and seismic data illustrate this calibrated seismic approach.
It is becoming popular to extract fracture information from wide-azimuth P-P reflection seismic data. The extracted crack density is not influenced by the phase of the seismic data. The extracted fracture orientation is sensitive to the phase of seismic data and the nature of the rocks. Other information besides the amplitude and NMO velocity of seismic data is needed in order to uniquely determine the fracture orientation. This paper discusses the ambiguity of the fracture orientation and how it can be resolved. Todorovic-Marinic et al (2004) discussed the stabilization of crack density.
Qualitative examination of half-space rock and fluid properties reveals that hydrocarbon-filled porosity causes bright spots and increasing AVO (amplitude-versus-offset) slope that seismically illuminates the King Field, Gulf of Mexico. Fluid substitution modeling indicates that replacing the oil with brine reduces the reflection strength to background noise levels, thereby removing the AVO anomaly. By incorporating thickness and amplitude scaling into well-log-based AVO modeling, we were able to quantify the influence of tuning and amplitude scaling. The resulting suite of modeled AVO signatures can be used to calibrate AVO attributes extracted from real data.
DeVault, Bryan (Colorado School of Mines, presently Nederlandse Aardolie Maatschappij) | Davis, Thomas L. (Texaco EPTD) | Tsvankin, Ilya (Colorado School of Mines) | Sukup, Dwight (Colorado School of Mines) | Hilterman, Fred (Geophysical Development Corporation) | Verm, Richard (Geophysical Development Corporation)
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