Claims:1. A method of detecting hydrocarbons in earth using seismic signals, wherein the seismic signals are obtained by a plurality of receivers at a second seismic location responsive to acoustic signals imparted into the earth by a plurality of transmitters at a first seismic location, wherein the seismic signals are used for determining Amplitude Variation with Offset (AVO) attributes which facilitates in detecting the hydrocarbons in the earth, the method comprising:
determining a variation of reflection coefficient of a reflected P-wave with a plurality of incidence angles created between the reflected P-wave and an incident P-wave, wherein the reflected P-wave is reflected of a plurality of rocks in the earth, wherein the variation is determined using one or more reflector models;
selecting a set of discrete incidence angles from the plurality of incidence angles for generating one or more discrete Amplitude Variation with Angle (AVA) curves;
determining one or more elastic rock properties attributes for each of the one or more reflector models;
generating a rock property dataset (P) comprising the one or more elastic rock properties attributes and the one or more reflector models;
obtaining a discrete basis dataset (BMAVO) using a reflection coefficient dataset (Rpp) and a modified rock property dataset (P-1), wherein the reflection coefficient dataset (Rpp) comprises the one or more discrete AVA curves and the one or more reflector models, wherein the modified rock property dataset (P-1) is obtained by modifying the rock property dataset (P), wherein the discrete basis dataset (BMAVO) is used to determine a rock properties dataset (M) and an approximate variation of reflection coefficients with the plurality of incidence angles using reflected P-wave seismic signals received in real-time, wherein the one or more properties of the plurality of rocks and the approximate variation are used to detect hydrocarbons.

2. The method as claimed in claim 1, wherein the one or more elastic rock properties attributes comprises at least an intercept (I), a gradient (G) and a curvature (C).

3. The method as claimed in claim 1, wherein the one or more properties of the plurality of rocks are used as Direct Hydrocarbon Indication (DHI).

4. The method as claimed in claim 1, wherein the approximate variation of the reflection coefficient of the reflected P-wave seismic signals are determined based on a linear combination of (BMAVO) and the one or more elastic rock properties attributes.

5. The method as claimed in claim 1, wherein weights are associated with the one or more elastic rock properties, wherein the weights are used to determine the approximate variation.

6. The method as claimed in claim 1, wherein the discrete basis dataset (BMAVO) is inverted to determine the rock properties dataset (M).

7. An Amplitude Variation with Offset (AVO) system for detecting hydrocarbons in earth using seismic signals, wherein the seismic signals are obtained by a plurality of receivers at a second seismic location responsive to acoustic signals imparted into the earth by a plurality of transmitters at a first seismic location, wherein the seismic signals are used for determining Amplitude Variation with Offset (AVO) attributes which facilitates in detecting the hydrocarbons in the earth, the AVO system comprising:
a processor; and
a memory, communicatively coupled to the processor, storing processor executable instructions, upon being executed causes the processor to:
determine a variation of reflection coefficient of a reflected P-wave with a plurality of incidence angles created between the reflected P-wave and an incident P-wave, wherein the reflected P-wave is reflected of a plurality of rocks in the earth, wherein the variation is determined using one or more reflector models;
select a set of discrete incidence angles from the plurality of incidence angles for generating one or more discrete Amplitude Variation with Angle (AVA) curves;
determine one or more elastic rock properties attributes for each of the one or more reflector models;
generate a rock property dataset (P) comprising the one or more elastic rock properties attributes and the one or more reflector models;
obtain a discrete basis dataset (BMAVO) using a reflection coefficient dataset (Rpp) and a modified rock property dataset (P-1), wherein the reflection coefficient dataset (Rpp) comprises the one or more discrete AVA curves and the one or more reflector models, wherein the modified rock property dataset (P-1) is obtained by modifying the rock property dataset (P), wherein the discrete basis dataset (BMAVO) is used to determine a rock properties dataset (M) and an approximate variation of reflection coefficients with plurality of incidence angles using reflected P-wave seismic signals received in real-time, wherein the one or more properties of the plurality of rocks and the approximate variation are used to detect hydrocarbons.

8. The AVO system as claimed in claim 7, wherein the one or more elastic rock properties attributes comprises at least an intercept (I), a gradient (G) and a curvature (C).

9. The AVO system as claimed in claim 7, wherein the one or more properties of the plurality of rocks are used as Direct Hydrocarbon Indication (DHI).

10. The AVO system as claimed in claim 7, wherein the processor determines the approximate variation of the reflection coefficient of the reflected P-wave seismic signals based on a linear combination of (BMAVO) and the one or more elastic rock properties attributes.

11. The AVO system as claimed in claim 7, wherein the processor is configured to associate weights with the one or more elastic rock properties, wherein the weights are used to determine the approximate variation.

12. The AVO system as claimed in claim 7, wherein the processor is configured to invert the discrete basis dataset (BMAVO) to determine the rock properties dataset (M).

Dated this 18th Day of December, 2018

Madhusudan S T
IN/PA-1297
Of K & S Partners
Agent for the Applicant
, Description:
TECHNICAL FIELD
The present disclosure relates to the direct hydrocarbon indication using Amplitude Variation with Offset (AVO). More particularly, but not exclusively, the present disclosure relates to a method and a system for detecting hydrocarbons in earth by using discrete basis function.

BACKGROUND
The properties/characteristics of rocks are studied to detect hydrocarbons in the earth. Generally, a plurality of transmitters transmits seismic signals into the earth. A part of the seismic signals is reflected off the rocks and are received by a plurality of receivers. The plurality of transmitters and the plurality of receivers are separated by specific distances. The received seismic signals are processed to study the rock properties, thereby detecting hydrocarbons.

Amplitude Variation with Offset (AVO) is an important aspect to understand lithology and fluid variation in sub-surface of the earth. The mathematical basis of AVO is based on the Zoeppritz equations. The Zoeppritz equations are very complex to analyse pre-stack seismic reflections and interpret the characteristics of rocks. Hence, the Zoeppritz equations are simplified and approximated AVO equations are derived known as Aki-Richard equations. However, the Aki-Richards equations deviate from Zoeppritz equations for higher incidence angles. Also, the Aki-Richard equations make certain assumptions which is are not suitable for AVO analysis in presence of high impedance contrast between two layers in the earth (for example in presence of salt domes, basalts, glaciological applications, heavy oil fields, hard calcareous sands, low porosity sands, and the like). Figure 1 shows a comparison of the Aki-Richard response and Zoeppritz response for a class 1 sand. As seen in the figure 1, it is evident that at higher angles Aki-Richard response (2nd term) (103) and (3rd term) (102) though simplified and linearized but approximated, fairs poorly with respect to the Zoeppritz response (101). The viriation in Aki-Richard response is severe in class 1 sand because of the presence of critical reflection, which affects the Zoeppritz response (101) beyond 35° in this case and is shown in Figure 1.

Zoeppritz equations cannot be simplified analytically without making drastic assumptions. Such assumptions shall poorly replicate the original behaviour of the rocks. Further, for different sub-surface different sets of rock properties are required. However, to overcome limitations of Zoeppritz equations, many other approximations of the Zoeppritz equations are derived. But, none of the approximated equations provide accurate AVO analysis at higher angles. Thus, conventional techniques do not provide a single equation that can be used for different sub-surfaces or a model that replicates close to Zoeppritz.

The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

SUMMARY
In an embodiment, the present disclosure relates to a method and a system for detecting hydrocarbons in earth using seismic signals. A plurality of P-waves is incident into the earth. A part of the incident P-wave is reflected off a plurality of rocks present in the earth. The method comprises determining a variation of reflection coefficient between the reflected P-wave with the plurality of incident P-waves. The variation is determined using one or more reflector models. Further, a set of discrete incidence angles are selected from the plurality of incidence angles for generating one or more discrete Amplitude Variation with Angles (AVA) curves. Thereafter, one or more elastic rock properties attributes are determined for each of the one or more reflector models. Furthermore, a rock property data set (P) is generated, comprising the one or more elastic rock properties attributes and the one or more reflector models. Further, a discrete basis data set (BMAVO) is obtained using a reflection coefficient dataset (Rpp) and a modified rock property dataset (P-1). The reflection coefficient dataset (Rpp) comprises the one or more discrete AVA curves and the one or more reflector models. The modified rock property dataset (P-1) is obtained by modifying the rock property dataset (P). The discrete property dataset (BMAVO) is used to determine a real-time rock property dataset (M) and an approximate variation of reflection coefficients with the plurality of incidence angles using the reflected P-wave seismic signals. The real-time rock properties dataset (M) is used to detect hydrocarbons.

The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
The novel features and characteristic of the disclosure are set forth in the appended claims. The disclosure itself, however, as well as a preferred mode of use, further objectives and advantages thereof, will best be understood by reference to the following detailed description of an illustrative embodiment when read in conjunction with the accompanying figures. One or more embodiments are now described, by way of example only, with reference to the accompanying figures wherein like reference numerals represent like elements and in which:

Figure 1 illustrates AVA response generated in accordance with conventional techniques;

Figure 2 illustrates an exemplary block diagram of an AVO system for detecting hydrocarbons, in accordance with an embodiment of the present disclosure;

Figure 3 illustrates an exemplary flowchart for detecting hydrocarbons, in accordance with an embodiment of the present disclosure;

Figure 4 illustrates comparison of rock properties attributes curves generated using proposed technique with conventional techniques, in accordance with an embodiment of the present disclosure;

Figure 5 illustrates comparison of AVO response at mean values, generated using proposed technique with conventional techniques, in accordance with an embodiment of the present disclosure;

Figure 6 illustrates comparison of AVO response at upper extreme values, generated using proposed technique with conventional techniques, in accordance with an embodiment of the present disclosure;

Figure 7 illustrates comparison of AVO response at lower extreme values, generated using proposed technique with conventional techniques, in accordance with an embodiment of the present disclosure;

Figure 8a and 8b illustrates comparison between intercept determined using conventional technique and intercept determined using proposed technique, in accordance with an embodiment of the present disclosure;

Figure 9a and 9b illustrates comparison between gradient determined using conventional technique and gradient determined using proposed technique, in accordance with an embodiment of the present disclosure;

Figure 10a and 10b illustrates comparison between curvature determined using conventional technique and curvature determined using proposed technique, in accordance with an embodiment of the present disclosure; and

Figure 11a and 11b illustrates comparison between density across an interface determined using conventional technique and density across an interface determined using proposed techniques.

It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION
In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the scope of the disclosure.

The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.

Embodiments of the present disclosure relate to a method and a system for detecting hydrocarbons in earth. In a typical hydrocarbon detection technique, a plurality of seismic waves is incident into the earth from a first seismic location using a plurality of transmitters. The incident waves are reflected and refracted due to presence of rocks and other obstacles in the earth. The reflected waves are collected by a plurality of receivers located at a second seismic location. The received waves are processed to detect hydrocarbons.

The proposed method comprises determining a variation of reflection coefficient of a reflected P-wave with a plurality of incidence angles created between the reflected P-wave and a plurality of incident P-waves. The variation may be determined using one or more reflector models. Further, a discrete set of incidence angles are selected from the plurality of incidence angles for generating one or more Amplitude Variation with Angle (AVA) curves. Furthermore, one or more elastic rock properties attributes are determined for each reflector model. Thereafter, a rock property dataset (P) is generated comprising the one or more elastic rock properties attributes and the one or more reflector models. Further, a reflection coefficient dataset (RPP) is determined using the one or more discrete AVA curves and the one or more reflector models. Also, a modified rock property dataset (P-1) is determined by inverting the rock property dataset (P). Lastly, the (RPP) and the (P-1) are used to calculate a discrete basis dataset (BMAVO). The (BMAVO) is then used to calculate real-time rock properties dataset (M). Thus, the proposed method provides AVO responses close to AVO response obtained using Zoeppritz technique and thereby leading to improved Hydrocarbon Indicator.

Figure 2 illustrates a block diagram of an Amplitude Variation with Offset (AVO) system (200). The AVO system (200) may include at least one Central Processing Unit (“CPU” or “processor”) (208) and a memory (209) storing instructions executable by the at least one processor. The processor (208) may comprise at least one data processor for executing program components for executing user or system-generated requests. The memory (209) is communicatively coupled to the processor (208). The AVO system (200) may further comprise an Input/ Output (I/O) interface (210). The I/O interface (210) may be coupled with the processor (208) through which an input signal or/and an output signal is communicated.

The AVO system (200) comprises a variation detector (201), a selection module (202), an attributes determination module (203), a rock property dataset generator (204), an AVA generator (205), a reflector coefficient dataset generator (206) and a discrete basis dataset generator (207).

In an embodiment, the variation detector (201) is configured to detect a variation in reflection coefficient in reflected P-waves from the plurality of incident P-waves. When the plurality of P-waves is incident using a plurality of transmitters, the incident P-waves gets reflected by rocks in the earth. The reflected P-waves are collected by the plurality of receivers. The variation detector (201) determines how much the reflected P-waves have varied from the incident P-waves. To determine the variation, the variation detector (201) may determine a reflection coefficient of the reflected P-waves. In an embodiment, the reflection coefficient and the variation may be determined using one or more reflector models.

In an embodiment, the selection module (202) is configured to select a set of discrete incidence angles from the plurality of incidence angles. For the discrete incidence angles, amplitude of the reflected P-waves is measured to generate AVA curves. The AVA curves are used to determine how the amplitude of the reflected P-waves vary with change in incidence angles. In an embodiment, the AVA curves are generated by the AVA generator (205).

In an embodiment, the attributes determination module (203) is configured to determine one or more elastic rock properties attributes. The one or more elastic rock properties attributes comprises at least one of an intercept (I), a gradient (G) and a curvature (C). The one or more rock properties attributes are defined in Aki-Richard AVO equation as given in equation (1):
R(?) = A + Bsin2 ? + Csin2?tan2? (1)
Where,
A = intercept;
B = gradient; and
C = curvature.

In an embodiment, the A, B and C may be determined using Aki-Richard equation. In an alternate embodiment, the A, B and C may be determined using the one or more reflector models.

In an embodiment, the rock property dataset generator (204) is configured to generate a rock property dataset (P). The rock property dataset (P) comprises the one or more rock properties attributes (A, B, C) and the one or more reflector models. In an embodiment the rock property dataset generator (204) may also generate an inverse of the rock property dataset (P). The inverse of the rock property dataset (P) is referred as modified rock property dataset (P-1).

In an embodiment, the reflection coefficient dataset generator (206) is configured to generate a reflection coefficient dataset (RPP). The (RPP) may comprise the one or more AVA curves and the one or more reflector models.

In an embodiment, the discrete basis dataset generator is configured to generate a discrete basis dataset (BMAVO). The (BMAVO) is generated using the (Rpp) and the (P-1). The rock property dataset (P) is generated using models, which may not be appropriate for real-time analysis. The models may only provide approximations for a particular well and may not be accurate. The (BMAVO) is generated to determine real-time rock property dataset (M) for a particular well. The real-time rock property dataset (M) thus provides accurate data about the rocks in the seismic location. The accurate data is used to detect hydrocarbons with increased accuracy.

In an embodiment, all modules used herein refers to an application specific integrated circuit (ASIC), an electronic circuit, a field-programmable gate arrays (FPGA), Programmable System-on-Chip (PSoC), a combinational logic circuit, and/or other suitable components that provide the described functionality. The modules when configured with the functionality defined in the present disclosure will result in a novel hardware.

Figure 3 shows a flow chart illustrating a method for detecting hydrocarbons, in accordance with some embodiments of the present disclosure.

As illustrated in Figure 3, the method 300 may comprise one or more steps for detecting hydrocarbons in earth, in accordance with some embodiments of the present disclosure. The method 300 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions or implement particular abstract data types.

The order in which the method 300 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the spirit and scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

At step 301, the variation detector (201) determines a variation of the reflection coefficient of the reflected P-waves with the plurality of incidence angles created between the reflected P-waves and the plurality of incident P-waves. The variation of the reflection coefficient of the reflected P-waves with the incidence angles is determined to identify if the reflected P-waves are varying with different incidence angles. In an embodiment, the variation may be determined using one or more reflector models.

At step 302, the selection module (202) selects a set of discrete angles from the plurality of incidence angles for generating the one or more AVA curves. The AVA curves indicate variation of amplitude of the reflected P-waves with change in incidence angles. The AVA curves are used to study patterns in variation of the reflected P-waves with incidence angles.

At step 303, the attributes determination module (203) determines one or more elastic rock properties attributes for each of the one or more reflector models. As shown in equation (1), a common expression of the AVA response using Aki-Richard equation is shown. AN expanded equation of equation (1) is given below in equation (2):

(2)

Where,

Intercept A =

Gradient B =

Curvature C =

In an embodiment, the elastic rock properties are used to determine P-wave velocity, S-wave velocity and density. In conventional techniques, the curvature (C) is often neglected, thus accurate rock properties are not obtained. However, the proposed method and system makes use of the curvature (C) parameter to obtain accurate rock properties.
In an embodiment, the equation (1) may be represented as shown in equation (3):
RAR = BARP (3)
Where,
RAR = reflection coefficient of PP-wave (reflected P-wave for incident P-wave);
BAR = basis dataset based on Aki-Richard equation

At step 304, the rock property dataset generator (204) generates the rock property dataset (P). The (P) dataset comprises the one or more elastic rock properties (A, B, C) determined at step 303.
At step 305, the basis matrix is obtained as given in below equation (4):

Rm = BMAVOP (3)
BMAVO = RmP-1 (4)

The proposed model as shown in equation (4) is then used to determine real-time rock property dataset (M). The proposed model is now compared with conventional techniques. Hilterman Class -1 model elastic properties for water-sand and gas-sand is considered for comparing AVO response of conventional techniques with AVO response of proposed technique. Table 1 shows the Hilterman Class-1 model values for class-1 gas-sand and water-sand.

TABLE 1

Referring to Figure 4, a comparison between the basis functions for A, B, C derived using the proposed model and the A, B, and C derived using the conventional technique. As seen, the curvature (C) (404) derived using conventional technique (Aki-Richard equation) and the curvature (C) (406) derived using the proposed model have different response. Similarly, the intercept (A) (401) and the gradient (B) (403) derived using conventional technique deviate from the intercept (A) (402) and the gradient (B) (405) derived using the proposed technique.
Reference is now made to Figure 5, where responses from Aki-Richard 2nd term (502) and 3rd term (503), response from Zoeppritz equation (501) and response from the proposed technique (504) are compared. As seen, the response from the proposed technique (504) lies closer to the response from Zoeppritz technique (501) with different incidence angles. In this comparison, mean values of simulated rock properties are considered.

Reference is now made to Figure 6, where responses from Aki-Richard 2nd term (602) and 3rd term (603), response from Zoeppritz equation (601) and response from the proposed technique (604) are compared. As seen, the response from the proposed technique (604) lies closer to the response from Zoeppritz technique (601) with different incidence angles. In this comparison, upper extreme values of simulated rock properties are considered.

Reference is now made to Figure 7, where responses from Aki-Richard 2nd term (702) and 3rd term (703), response from Zoeppritz equation (701) and response from the proposed technique (704) are compared. As seen, the response from the proposed technique (704) lies closer to the response from Zoeppritz technique (701) with different incidence angles. In this comparison, lower extreme values of simulated rock properties are considered.

Figure 8a and 8b illustrates comparison between intercept determined using conventional technique and intercept determined using proposed technique, in accordance with an embodiment of the present disclosure.

Figure 9a and 9b illustrates comparison between gradient determined using conventional technique and gradient determined using proposed technique, in accordance with an embodiment of the present disclosure.

Figure 10a and 10b illustrates comparison between curvature determined using conventional technique and curvature determined using proposed technique, in accordance with an embodiment of the present disclosure.

Figure 11a and 11b illustrates comparison between density across an interface determined using conventional technique and density across an interface determined using proposed techniques.

In an embodiment, the Aki-Richard AVA response in case of class 1 sand can replicate the plane wave Zoeppritz response up-to incidence angle 25 degree to 35 degree. However, as the angle of incidence increases and approaches the critical angle, Aki-Richard AVA response is inadequate to capture the Zoeppritz response as shown in Figure (1). Moreover, the Zoeppritz response for different classes of AVO is so varied and complex that deriving a single analytical yet simple and intuitive modification of Zoeppritz response which is equally efficient for all classes of AVO is difficult. For example, curvature, density AVA attributes which depend on higher incidence angle, may make way for more insightful interpretation of the rock properties of the well/ reservoir but the limitations of the conventional method restricts its usage because of it poor quality. The proposed approach for class 1 may be useful to capture the Zoeppritz AVA response even when the incidence angle approaches critical angle. The AVA attributes obtained from proposed approach has considerable noise reduction in gradient, curvature and density. In addition, the synthetic seismic correlation corresponding to the AVA attributes is improved dramatically, in case of curvature, the synthetic seismic correlation is improved from -0.03 to 0.9. The proposed AVA approach may be used to directly obtain any rock property combination rather than to first solve for traditional AVA attributes A, B, C and then combine the rock property combination to obtain the desired rock properties. For example, basis function corresponding to P-wave reflectivity, S-wave reflectivity and density reflectivity can be directly obtained using the proposed approach.

The terms "an embodiment", "embodiment", "embodiments", "the embodiment", "the embodiments", "one or more embodiments", "some embodiments", and "one embodiment" mean "one or more (but not all) embodiments of the invention(s)" unless expressly specified otherwise.

The terms "including", "comprising", “having” and variations thereof mean "including but not limited to", unless expressly specified otherwise.

The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise. The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.

A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.

When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.

The illustrated operations of Figure 3 show certain events occurring in a certain order. In alternative embodiments, certain operations may be performed in a different order, modified or removed. Moreover, steps may be added to the above described logic and still conform to the described embodiments. Further, operations described herein may occur sequentially or certain operations may be processed in parallel. Yet further, operations may be performed by a single processing unit or by distributed processing units.

Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.

While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

REFERRAL NUMERALS:
Reference number Description
200 AVO system
201 Variation Detector
202 Selection Module
203 Attributes Determination Module
204 Rock Property Dataset Generator
205 AVA Generator
206 Reflection Coefficient Dataset Generator
207 Discrete Basis Dataset Generator