AVO Technology Research Articles

AVO Attribute Characteristics of Ground Penetrating Radar

As a non-destructive and high-efficiency electromagnetic wave exploration method, the conventional fixed-offset GPR detection has been able to solve some practical problems. However, in the case of complex formation conditions and variable physical parameters, the effect is not too ideal. In reference to earthquakes, AVO processing technology can be used to enhance the detection of lithologic parameters. This paper introduces the application of AVO in GPR by numerical simulation. By controlling variables and changing the parameters of the model, the response characteristics under different offsets and different relative dielectric constants are analyzed, and the application of AVO technology in radar processing and the identification of lithologic parameters of the lower interface are verified.

Discrimination of AVO Types in Shallow Reservoirs Based on Random Forest Algorithm

As we all know, AVO technology can be used to identify gas-bearing reservoirs and is of great significance to oil and gas exploration. The manual identification of AVO types of reservoirs has large human interference factors, low identification accuracy and long time-consuming. Therefore, this paper introduces the random forest algorithm, uses bootstrap repeated sampling and branch and leaf node splitting techniques to generate a large number of decision tree classifiers, and realizes the identification of the AVO type of the reservoir by counting the classification results of all decision trees. Firstly, a velocity density model is established based on logging data in the working area. Secondly, use the Shuey approximation formula to calculate the AVO curve and obtain the fitted polynomial corresponding to the curve. Thirdly, the morphological feature parameters are extracted according to the fitting polynomial as the input parameters of the training data set of the random forest algorithm, and the artificial AVO type recognition results are used as the output parameters to train and obtain a decision tree classifier. Finally, using the characteristic parameters of the AVO curve of the actual pre-stack seismic data as input parameters, the classification of the AVO type of the reservoir in the working area is obtained through the classification of the random forest decision tree. By comparing the results with the approximate support vector machine algorithm, it can be seen that the two algorithms approximate the AVO type discrimination results of the reservoir, and both have high accuracy, but the random forest algorithm requires fewer feature attributes, shows stronger generalization and has better universality.

Using frequency-dependent AVO inversion to predict the “sweet spots” of shale gas reservoirs

Abstract Shale gas is an unconventional hydrocarbon resource with huge potential. Using geophysical methods to predict “sweet spots” is the key to commercial exploration of shale gas. At present AVO technology is one of most widely used geophysical techniques to find shale gas reservoirs with high abundance. However, the effects of the dispersion of actual mediums are neglected by conventional AVO inversion. Recent experiments have shown that in gas-bearing strata, the dispersion may be rather remarkable. In this paper, we develop a frequency-dependent AVO inversion scheme, which includes seismic dispersion in real rock medium, to predict the “sweet spots” of shale gas reservoirs. Application of the inversion has been made to the shale gas in the south of Jiaoshiba area to test the validity. Comparing the results of the frequency-dependent AVO inversion and well production, we find that regions with high dispersion gradients correlate well with places with high production of shale gas. Therefore we conclude that the frequency-dependent AVO may be a workable approach to detect the “sweet spots” of shale gas reservoirs.

Applying accurate gradients of seismic wave reflection coefficients (SWRC) to the inversion of seismic wave velocities

Through solving the Zoeppritz’s partial derivative equations, we have obtained accurate partial derivatives of reflected coefficients of seismic wave with respect to P- and S-wave velocities. With those partial derivatives, a multi-angle inversion is developed for seismic wave velocities. Numerical examples of different formation models show that if the number of iterations goes over 10, the relative error of inversion results is less than 1%, whether or not there is interference among the reflection waves. When we only have the reflected seismograms of P-wave, and only invert for velocities of P-wave, the multi-angle inversion is able to obtain a high computation precision. When we have the reflected seismograms of both P-wave and VS-wave, and simultaneously invert for the velocities of P-wave and VS-wave, the computation precisions of VS-wave velocities improves gradually with the increase of the number of angles, but the computation precision of P-wave velocities becomes worse. No matter whether the reflected seismic waves from the different reflection interface are coherent or non-coherent, this method is able to achieve a higher computation precision. Because it is based on the accurate solution of the gradient of SWRCs without any additional restriction, the multi-angle inversion method can be applied to seismic inversion of total angles. By removing the difficulties caused by simplified Zoeppritz formulas that the conventional AVO technology struggles with, the multi-angle inversion method extended the application range of AVO technology and improved the computation precision and speed of inversion of seismic wave velocities.

Research andTLE

In this the 20th year of TLE, the Editorial Board has decided to publish a series of 12 articles reviewing how TLE has reported specific areas of geophysics since its inception in 1982. This month's topic is research. In the last 20 years, there has been considerable change in how we define and conduct research in our industry. In the “old days,” budgets in major oil companies included a large allocation for conducting basic research—i.e., research groups (populated by highly sought PhDs from the world's major universities) investigating ideas with a long-term focus or conducting expensive, specialized field experiments, or even developing new hardware on their own. And it didn't end there. Research on fundamental geophysical topics was conducted by contractors, academia, and government labs. Industry support for university research was strong and, at that time, researchers had strong influence in determining the relevant topics of research to be investigated. We see the many visible fruits of such an approach to research: advances in 3D seismic acquisition and processing, AVO, crosswell and VSP technology to mention just a few.

Abstract: A Technology to Extract Lithology, Porosity and Hydrocarbon Content from Conventional Seismic Data 

ABSTRACT The quantification of lithology, fluids, and structure are the definitive goals of seismic exploration. Exploitation of amplitude information only, although sufficient for many structural interpretations, fails in the ability to adequately define lithology. Conventional post-stack inversion technology, while quantifying rock property information in the form of acoustic impedance, velocity, or density, conveys little in the way of definitive mineral or fluid information. For example, a low velocity interval from an inversion may be interpreted as either a porous sand reservoir or a slow shale, with obviously different drilling results. AVO technology exploits the loss or gain in reflected P-wave energy due to shear wave conversion at interfaces. Although AVO measurements from pre-stack seismic data contain fluid and lithology information, conventional AVO gradient products fail to provide quantification of lithology or fluids. We present a technology for extracting detailed lithology, porosity and hydrocarbon content sections from conventional seismic data through a unique combination of AVO and seismic inversion technologies. The method has been in use for several years and successfully decomposes sand, shale, and carbonate lithologies including gas/oil fluid content and effective reservoir porosity. Current research is successfully extending the technique to quantify salts and coals.

AVO processing calibration

Over the years AVO technology has been successfully employed in different sedimentary environments. The technique is normally used for lithology discrimination, but in many cases it has been used as an effective direct hydrocarbon indicator. Despite the enormous success, there have been some failures.

Abstract: Impact of 3D and Avo Technology to Exploration Efforts in Deepwater Nigeria

Abstract: Impact of 3D and Avo Technology to Exploration Efforts in Deepwater Nigeria