Amplitude Versus Offset Attributes Research Articles

AVO study on a known geothermal reservoir located in the fractured carbonate formations of the pre-Cenozoic basement, Northwest Hungary

Amplitude Versus Offset (AVO) analysis has been successfully applied in the hydrocarbon industry for more than three decades. This effective tool of the joint seismic and well-log data processing enables to predict and analyze fluid saturated porous geological formations. AVO methodology is based on the anomalous behavior of the pre-stack reflected amplitudes observed from fluid bearing rocks. However, the potential of AVO methodology is still unexploited in geothermal exploration, although the lithology and rock physical properties are very similar. In this study, we summarize the theoretical backgrounds and calculate synthetic AVO responses of a known geothermal reservoir located in the fractured carbonates of the Mesozoic basement. We demonstrate that the AVO response of a deep geothermal reservoir can be quite different from the amplitude response observed from a hydrocarbon bearing clastic formation. AVO attributes of the investigated geothermal reservoir are presented, and the potential of its detection by seismic amplitude data are discussed.

Detection of hydrocarbon- saturated reservoirs in a challenging geological setting using AVO attributes: A case study from Poseidon field, Offshore Northwest region of Australia

Amplitude Versus Offset (AVO) methods relate seismic amplitude variations to subsurface pore fluid and lithology changes. Over the past decades, numerous AVO attributes have been extracted from seismic data and combined to detect seismic expressions associated with hydrocarbon-charged sediments. In this paper, we use an AVO attribute combination composed of gradient and scaled-Poisson reflectivity (SPR) to detect hydrocarbon expressions. Irrespective of sand-shale impedance contrast, the SPR and the gradient G produce negative anomalies for shale over gas saturated reservoir. We demonstrate that SPR-G product is a good alternative to the Intercept-Gradient product which works only for unconsolidated sands. The dataset used in this study is from Poseidon field, North Western Australia. The gas reservoirs belong to the Middle Jurassic-aged Plover Formation. The Plover Formation comprises sandstone, mudstone, and coal that deposited in a fluvial-deltaic environment. AVO analysis at a well location indicates the reservoirs belong to AVO Class II, which is characterized by small zero offset reflectivity and an anomalously large G. Due to the low impedance contrast between the reservoirs and the shale intervals, the I × G product failed to detect the fluid expressions of the reservoirs. The SPR × G product and SPR-G crossplot showed better fluid detection and lithology discrimination. Furthermore, the computation of the product SPR × G volume helped highlight the fluid response and spatial distribution of the reservoir units. New prospective undrilled areas could be identified using the SPR-G product.

Application of AVO to thickness prediction of thin sand

Oil and gas are the resource buried in deep underground. The purpose of petroleum exploration is to delineate the sand body saturated with the oil or gas. The thickness of sand is an important property of sand layer in the reservoir research. In the oilfield of Eastern China, the thickness of sand body is usually very thin and below ten meters, so it is very hard for us to estimate the real thickness of sand body because its thickness is far less than the resolution limit of seismic wavelet in exploration. For further discussion of the problem, we probed into how to use the method of amplitude versus offset (AVO) to predict the thickness of sand body in this paper. Firstly, a set of thin sand models with different thickness are made; then, the prestack gathers of the models are simulated with the reflectivity method; after that, AVO attributes of prestack gathers are analyzed; next, the relationship between AVO attributes and the thickness of thin sand are established; finally, the relationship is used for the prestack gathers of the entire seismic data, and the thickness of thin sand of study area are estimated.

New AVO Attributes and Their Applications for Facies and Hydrocarbon Prediction: A Case Study from the Northern Malay Basin

Amplitude versus offset (AVO) analysis integration to well log analysis is considered one of the advanced techniques to improve the understanding of facies and fluid analysis. Generating AVO attributes are one solution to give an accurate result in facies and fluid characterization. This study is focused on a field of Northern Malay basin, which is associated with a fluvial-deltaic environment, where this system has high heterogeneity, whether it is vertically or horizontally. This research is aimed to demonstrate an application of the scale of quality factor of P-wave (SQp) and the scale of quality factor of S-wave (SQs) AVO attributes for facies and fluid types separation in field scale. These methods are supposed to be more sensitive to predict the hydrocarbons and give less ambiguity. SQp and SQs are the new AVO attributes, which derived from AVO analysis and created according to the intercept product (A) and gradient (B). These new attributes have also been compared to the common method, which is the Scaled Poisson’s Ratio attribute. By comparing with the Scaled Poisson’s Ratio attribute, SQp and SQs attributes are more accurate in determining facies and hydrocarbon. SQp and SQs AVO attributes are integrated with well log data and considered as the best technique to determine facies and fluid distribution. They are interpreted by using angle-stack seismic data based on amplitude contrast on interfaces. Well log data, e.g., density and sonic logs, are used to generate synthetic seismogram and well tie requirements. The volume of shale, volume of coal, porosity, and water saturation logs are used to identify facies and fluid in well log scale. This analysis includes AVO gradient analysis and AVO cross plot to identify the fluid class. Gassmann’s fluid substitution modeling is also generated in the well logs and AVO synthetics for in situ, pure brine, and pure gas cases. The application of the SQp and SQs attributes successfully interpreted facies and fluids distributions in the Northern Malay Basin.

An integrated petrophysical-based wedge modeling and thin bed AVO analysis for improved reservoir characterization of Zhujiang Formation, Huizhou sub-basin, China: A case study

AbstractThe main reservoir in Huizhou sub-basin is Zhujiang Formation of early Miocene age. The petrophysical analysis shows that the Zhujiang Formation contains thin carbonate intervals, which have good hydrocarbon potential. However, the accurate interpretation of thin carbonate intervals is always challenging as conventional seismic interpretation techniques do not provide much success in such cases. In this study, well logs, three-layer forward amplitude versus offset (AVO) model and the wedge model are integrated to analyze the effect of tuning thickness on AVO responses. It is observed that zones having a thickness greater than or equal to 15 m can be delineated with seismic data having a dominant frequency of more than 45 Hz. The results are also successfully verified by analyzing AVO attributes, i.e., intercept and gradient. The study will be helpful to enhance the characterization of thin reservoir intervals and minimize the risk of exploration in the Huizhou sub-basin, China.

Increasing resolution in the North Sea

Recent step changes in seismic processing and imaging technology have delivered dramatic improvements in resolution, velocity model building and multiple attenuation. This article will explore improvements in resolution that have been demonstrated on two multi-client surveys in the North Sea: Cornerstone and Northern Viking Graben (NVG). Extending full-waveform inversion (FWI) to include absorption effects as well as velocity has delivered improved imaging, higher resolution and more reliable AVO products for the NVG survey, and this will now be applied to the reprocessed Cornerstone data. Both surveys cover more than 35,000 km2 each, so application of high-resolution processing sequences to these two data sets will deliver advanced high-resolution data over two large areas of the North Sea. The NVG survey was acquired using BroadSeis variable-depth streamers in conjunction with a broadband source to maximize the bandwidth. However, new developments in broadband processing, including ghost wavefield elimination (GWE) and bandwidth extension, can be extended to the reprocessing of conventionally-acquired data sets, which can now be uplifted to deliver data of almost similar quality to modern broadband data by mitigating many of the limitations of traditional acquisition. This is demonstrated by the reprocessing of the Cornerstone project in the Central North Sea. Although this survey was recently reprocessed in depth using multi-layer tomography, the rapid improvements in GWE, multiple and noise attenuation, velocity modelling and imaging in the last few years mean that it can still benefit from being reprocessed again. Modern processing techniques ensure compliance with amplitude versus offset (AVO) analysis, and AVO attributes are used for QC purposes during the processing flow to ensure that the final data sets can be used directly for reservoir characterization. The AVO attribute maps for Cornerstone shown later in this article have already delivered impressive high-resolution images of the Forties field

AVO forward modeling and attributes analysis for fluid’s identification: a case study

Since the four decades amplitude versus offset (AVO) analysis is used extensively in hydrocarbon exploration to discriminate the hydrocarbon fluids from background geology. Conventionally AVO analysis involves calculation of intercept and gradient from a linear fit of compressional wave reflection coefficient to the sine square of the angle of incidence. Mississauga formation of early cretaceous is the reservoir rock in the study area, contains hydrocarbons and condensates in the middle part. It is very difficult to discriminate hydrocarbon fluids from non pay zones due to small thickness and low quality of pay zone. AVO forward modeling is done to estimate and analyze various AVO derived attributes for the discrimination of hydrocarbon from background sand. After calculating the AVO attributes, appropriate pairs of these attributes are crossplotted so that the hydrocarbon and non-hydrocarbon facies cluster together for quick identification and interpretation. In intercept/gradient crossplot the top of the gas zone falls in quadrant II and show clear deviation from background trend. The analysis reveals that oil and gas sand attributes are strongly different from water sand attributes. Among various attributes, the fluid factor and intercept are more promising attribute for fluid discrimination.

Precise 3D seismic steering and production rates in the Wilrich tight gas sands of West Central Alberta

We evaluate the controls on production performance of the Wilrich tight gas sand play in West Central Alberta, and show that careful steering using 3D seismic to place the wellbore within the upper reservoir is the most important geophysical contribution to production outcomes. Geologic, geophysical, drilling, and production data from more than 20 wells are used in the analysis. The completion and production parameters within the study area are relatively invariant, creating a control experiment relative to other productivity factors. We thus isolate the effects of varying bottom hole pressures, porosity, wellbore length, number of stimulations, mud gas response, gamma ray measurements while drilling, mud weight, curvature, amplitude versus offset (AVO), amplitude versus azimuth (AVAz), velocity versus azimuth (VVAz), and position of the horizontal wellbore within the reservoir. These variables are treated separately and in a multivariate fashion to determine their relative and combined effect on the productivity of the wells. Several methods of statistical evaluation are used to test confidence in the results. The Wilrich sand is approximately 20-m thick, and it was expected that the multistage fracture stimulation would have minimized the importance of vertical permeability variations by adequately accessing the entire vertical reservoir section. Such is not the case; precise placement of the wellbore in the most permeable stratigraphy of the thin reservoir is of material importance. The pressure and porosity strongly affect the production performance, but to a lesser degree than vertical position within the reservoir. This suggests that stratigraphic concerns as they relate to permeability variation can be critical, even in thin fracture-stimulated reservoirs. Interesting relationships were observed between the AVAz and curvature measures, but neither they nor the AVO or VVAz attributes yielded statistically significant correlations to the production data.

Seismic studies of coal bed methane content in the west coal mining area of Qinshui Basin

The coal bed methane content (CBMC) in the west mining area of Jincheng coalfield, southeastern Qinshui Basin, is studied based on seismic data and well-logs together with laboratory measurements. The results show that the Shuey approximation has better adaptability according to the Zoeppritz equation result; the designed fold number for an ordinary seismic data is sufficient for post-stack data but insufficient for pre-stack data regarding the signal to noise ratio (SNR). Therefore a larger grid analysis was created in order to improve the SNR. The velocity field created by logging is better than that created by stack velocity in both accuracy and effectiveness. A reasonable distribution of the amplitude versus offset (AVO) attributes can be facilitated by taking the AVO response from logging as a standard for calibrating the amplitude distribution. Some AVO attributes have a close relationship with CBMC. The worst attribute is polarization magnitude, for which the correlation coefficient is 0.308; and the best attribute is the polarization product from intercept, of which the correlation coefficient is −0.8136. CBMC predicted by AVO attributes is better overall than that predicted by direct interpolation of CBMC; the validation error of the former is 14.47%, which is lower than that of the latter 23.30%. CBMC of this area ranges from 2.5m3/t to 22m3/t. Most CBMC in the syncline is over 10m3/t, but it is below 10m3/t in the anticline; on the whole, CBMC in the syncline is higher than that in anticline.

Amplitude versus offset (AVO) analysis modelling in hydrocarbon exploration: A case study

In this study, the geological model used for amplitude versus offset (AVO) analysis, was created by synthetic well logs. The geological model is comprised of shale, gassy-sand, clay and sand layers. The synthetic seismic records including 230 shooting and 60 folds were constructed over the model. The data processing has been applied to the synthetic records. After the data processing, AVO analysis has been applied to synthetic data. Class III AVO anomaly has been obtained from the common depth point gathers. Also intercept, gradient, intercept* gradient and cross-plot attributes had been calculated. Analysis has shown that the amplitude increases with increasing offset. The gassy sand anomalies were also obtained by the AVO attributes. In addition, the advantages and disadvantages of AVO analysis were discussed in this study.   Key words: Geological model, reflection amplitude, reflection angle, hydrocarbon rock physics, amplitude versus offset attributes.

Integrated geological and geophysical analysis by hierarchical classification: combining seismic stratigraphic and AVO attributes

ABSTRACT The benefits of seismic attribute classification in subsurface studies have been published widely. The approach is usually the same and, in most cases, driven by a two-step procedure – an unsupervised classification and a supervised scheme where training is used to redefine classes based on well-log data flagging a specific fluid or lithology. In parallel to the multi-attribute analysis, interpreters have also benefited from recent advances in computing power, enabling the generation of multi-trace or texture attributes. In these two workflows, the focus is either on the seismic texture facies for seismic stratigraphic purposes, or on the reservoir facies for fluid and lithology mapping. This paper presents a case study in which both texture facies and fluid prediction are linked by performing a hierarchical classification scheme whereby a multi-attribute-based volume, which captures seismic texture information, is combined with amplitude versus offset (AVO) attributes to map fluid response into a single, coherent reservoir facies volume. This methodology is then applied for exploration data screening in offshore Borneo in the Greater Samarang sub-block (East Baram Delta, offshore Sabah, Malaysia). In this case study, the geological analysis, seismic geomorphology, seismic stratigraphy and combined fluid response from AVO attributes facilitate the development of new play concepts in the highstand system tracts and in the morphology generated by incised valleys in shoreface deposits.

Prediction of Shale Plugs between Wells in Heavy Oil Sands using Seismic Attributes

A fundamental geologic problem in the Steam-Assisted Gravity Drainage (SAGD) heavy oil developments in the McMurray Formation of Northern Alberta is to determine the location of shales in the reservoirs that may interfere with the steaming or recovery process. Petrophysical analysis shows that a key acoustic indicator of the presence of shale is bulk density. In theory, density can be derived from seismic data using Amplitude Versus Offset (AVO) analysis of conventional or multicomponent seismic data, but this is not widely accepted in practice. However, with billions of dollars slated for SAGD developments in the upcoming years, this technology warrants further investigation. In addition, many attributes can be investigated using modern tools like neural networks; so, the density extracted from seismic using AVO can be compared and combined with more conventional attributes in solving this problem. Density AVO attributes are extracted and correlated with “density synthetics” created from the logs just as the seismic stack correlates to conventional synthetics. However, multiattribute tests show that more than density is required to best predict the volume proportion of shale (Vsh). Vsh estimates are generated by passing seismic attributes derived from conventional PP, and multicomponent PS seismic, AVO and inversion from an arbitrary line following the pilot SAGD wells through a neural network. This estimate shows good correlation to shale proportions estimated from core. The results have encouraged the application of the method to the entire 3D.

Pressure‐dependent seismic response of fractured rock

Effects of external stress and pore pressure variations on the seismic signature of fractured rocks remain of interest to geoscientists and practicing geophysicists. Commonly, the effects are modeled theoretically, assuming fracture faces to be rough surfaces contacting each other via the surface asperities. The model proposed here differs from other models of this kind in that (1) fracture roughness is described by a single parameter and (2) a controlled degree of hydraulic connectivity between fractures and equant pores is introduced. This adds to the model's convenience and makes it applicable to a wide variety of reservoirs. The model predictions of seismic velocities in fractured rock at variable stress are consistent with experimental data. For fixed effective stress, the model predictions coincide with those obtained using the model with ellipsoidal fractures of certain average aspect ratio and the same fracture porosity.Apart from known effects, the model introduced predicts an amplification of the stress variation influence on fracturing‐induced anisotropy with an increase of connected equant porosity, a decrease of VP/VSwith effective stress, and implicit frequency dependence of the VP/VSrelation. It is also shown that amplitude versus offset (AVO) anomalies caused by fluid replacement can be seriously distorted if the fluid replacement is accompanied by significant variations of pore pressure, as, for example, at intense gas production. Neglecting these effects can lead to erroneous conclusions on shear modulus dependence on the pore fluid type. Qualitatively, in rocks with azimuthally aligned fracturing, the increase of effective stress affects AVO gradient in about the same way as the increase of water saturation parameter Vw. In contrast, the AVO intercept is not affected by variations of effective stress, while fluid replacement effect on the intercept is significant. Potentially, this can help distinguish the effects of pore pressure variations and fluid replacement on the AVO attributes.

Estimating and interpreting velocity uncertainty in migrated images and AVO attributes

Estimating a suitable velocity field for use in prestack depth migration is inherently uncertain because of limitations on the available data and estimation techniques. This uncertainty affects both the migrated depth of structures and their amplitudes in the inverted images. These effects can be estimated by performing multiple migrations with a set of velocity fields and colocating features in the migrated images. This lets us examine the imaging procedure’s sensitivity to changes in the velocity field so we can assess both structural and amplitude uncertainties in migrated images. These two types of uncertainties affect interpretation in different ways. For instance, with structural uncertainty interpretation we consider the change in migrated location of structures when deciding on drilling locations, optimizing well trajectories, or computing uncertainty in volumetric calculations. With amplitude uncertainty or amplitude versus offset (AVO) uncertainty interpretation, we consider (1) uncertainty in crossplots of pairs of AVO attributes at a point of interest or (2) uncertainty of the attribute values along identified structures. For any interpretation informing a decision, the uncertainty can help estimate risk. Our data processing approach is based on amplitude‐preserving prestack depth migration followed by AVO inversion, or AVO migration/inversion. It is valid for estimating AVO attributes in simple to moderately complex structural settings. Our methods of assessing the effect of velocity uncertainty can also be applied when obtaining structural uncertainties for a complex overburden geology or amplitude uncertainties in conventional NMO‐based AVO analysis. They may also be applied straightforwardly to any poststack attribute analysis. Key to the approach is the availability of multiple velocity fields to generate multiple migrated images. In our application, an automatic algorithm samples possible fields, but the set of fields to consider could be generated from another source, such as interpretation.