Seismic Inversion: Comparison Of Acoustic And Elastic Impedance Inversion Models For Rock Property Prediction

Project and Seminar Material for Geology

Seismic Inversion: Comparison Of Acoustic And Elastic Impedance Inversion Models For Rock Property Prediction


Abstract


Niger Delta is one of the major hydrocarbon producing basin in the world. This basin has a quite complex geology which makes routine seismic interpretation a challenging task for understanding the reservoir properties such as lithology and fluid content. Seismic inversion has proven to be a reliable tool for detailed understanding of the reservoir especially for lithological identification.

In this study, effort was made to compare acoustic and elastic impedance volumes with regards to litho-fluid discrimination in an offshore field in the Niger Delta. For this purpose, five horizons were interpreted to determine geological inputs for the impedance model building. Well log data was tied to a near post stack seismic volume and this was used in creating an initial acoustic impedance model. Thereafter, an initial elastic impedance model was created using well log data tied to a far post stack seismic volume. The initial elastic impedance model was created with an elastic impedance log generated at 360 which conforms to the incident angle for the far offset stack. Following analyses of the initial models at the well location, a full model-based acoustic and elastic impedance inversion was carried out separately for the entire area, using the interpreted horizons as controls.

The inverted results reveal reservoir tops and show lateral variations in lithology away from the well location. In particular, the elastic impedance inversion gave superior results only in areas where the acoustic impedance log used in inverting the near seismic volume is near constant through top reservoir transition. In areas where the acoustic impedance log could clearly distinguish the reservoir top, the acoustic and elastic impedance volumes gave comparable results. In comparison to the individual input seismic volumes, the inverted results would greatly improve reservoir property interpretation with possible integration with seismic stratigraphy.


Chapter One


Introduction

1.1 Background of Study

The development of structurally composite oil and gas fields requires a careful understanding of reservoir characterization so as to make the field performance more efficient. This requires combined scrutiny and understanding of the existing data such as seismic data and well log data. Seismic data make available vital information about the common geology of the area. However, extracting geological information such as porosity, density and shale volume is a great challenge for an interpreter. In seismic studies, seismic inversion is one of the great tools used in estimating detailed properties of the reservoir rock. Inversion is the process of extracting, from seismic data, the underlying geology which gave rise to that seismic (Hampson Russell).

The basic objective of seismic inversion is to transform seismic reflection data into a quantitative rock property, descriptive of the reservoir (Ogagarue, 2016). Conventionally, inversion has been applied to post-stack seismic data due to their ready availability with the aim of extracting acoustic impedance. In recent times, inversion has been extended to pre-stack seismic data, with the aim of extracting both acoustic and shear impedance. This allows the calculation of pore fluids.

During the last decades, several methods for estimating rock properties from seismic data were introduced and tested with the objective of providing further information for detailed reservoir characterization. The first deterministic inversion methods for acoustic impedance mapping were developed in the late 1970s and became known generally as recursive inversion (Lavergne and Willem, 1977; Lindseth, 1979).

Nowadays, most of the research efforts in this field are focused in the inversion and interpretation of variations of seismic reflection amplitude with change in distance between source and receiver (amplitude vs. offset) from pre-stack data. Because wells in a reservoir field are often spaced at hundreds or even thousands of meters, the ultimate goal of a seismic inversion procedure in the context of reservoir characterization is to provide models not only of acoustic impedance but also of other relevant physical properties, such as effective porosity and water saturation, for the inter-well regions. Such quantitative interpretations may sometimes require the use of other seismic attributes in addition to the traditional seismic reflection amplitudes (Rijks and Jauffred, 1991; Lefeuvre et al., 1995; Russell, 2004; Sancevero et al., 2005; Soubotcheva, 2006).

Diverse seismic inversion methods are viably used to map detailed reservoir rock properties such as lithology and fluid properties. These properties are estimated by using different inversion algorithms on the seismic data with erstwhile geological knowledge and well log data. The relationship between seismic and lithology is empirical. The reduction of uncertainty in this relationship will have large effect on the reservoir model building, thus on development and production of the hydrocarbon (Badri et al., 2002). The inverted impedance model is also used for building facies and facies-based porosity and permeability model (Shrestha et al., 2002).Seismic characteristics obtained from time, amplitude and frequency do not make available satisfactory information of reservoir properties on a layer by layer basis. Layer by layer information can be derived by means of stratigraphic inversion of post stack seismic data in terms of acoustic impedance.

There are many inversion techniques which are utilized in the industry for extraction of acoustic impedance from post stack seismic data, these techniques are band-limited, model based, and neural network nonlinear inversions (Russell, 1988, Duboz et al., 1998, Keys and Foster, 1998, Van Reil, 2000).


1.2 Statement of Problem

The global energy market is still determined to get more oil and gas. Greater demands for hydrocarbon in recent years caused oil and gas industry players to focus on deep offshore, and hot areas around the world. Even by overwhelming the geographical challenges there still remain serious challenging areas to deal with.

In addition to collecting and evaluating data quickly and competently, another challenge in the world of seismic exploration is the subsurface indistinctness which can be a difficult task in most regions. The best appearance of the subsurface is always considered for more precise and low- risk decision making, to reduce drilling risk (dry wells) and increase yield. Cutting-edge techniques provide enormous amount of information that can help to address the challenges which improves our interpretation of subsurface structures and also make known more facts about hydrocarbon prospects. Universal struggle for hydrocarbon continues to motivate the necessity to intensify exploration and boost recovery rate; nonetheless the cost of the operation is critically essential.

“Wells can measure several reservoir properties at high vertical resolution, but offer only sparse sampling laterally”, often at considerable cost (Russell, 1988). In addition difficulties arise; however, when we encounter poor wellbore condition or unexpected lithology or complexities related to subsurface structure. On the other hand, “seismic data provide nearly continuous lateral sampling at relatively low expense but with much less vertical resolution” (Russell, 1988). To address the challenges, seismic inversion for estimating the elastic properties was introduced.

It is the latest advancement in an integration approach which is the inverse modeling of the logs from seismic data.

The seismic reflection method was used initially as a useful tool for structure identification; some kind of structures could act as trap (such as anticline) for hydrocarbon reservoir (Russell et al, 2006). So much efforts have been made to improve our understanding of the amplitudes of seismic reflection data. It has been proved that a considerable amount of information is contained in seismic amplitude reflection that could be connected with porosity, lithology and even fluid change within the subsurface (Russell et al, 2006). Though seismic amplitude is equally a good indicator in the subsurface, several case studies depict that it is a vague indicator of hydrocarbon. In some cases, acoustic impedance alone may not be sufficient to quantify reservoir rock properties such as lithology and pore fluid, for an in-depth understanding of the reservoir. In order to obtain more accurate seismic reservoir characterization (also known as reservoir geophysics) all available seismic, petro-physical and geological information need to be integrated into volumetric distribution of reservoir properties like porosity and saturation. Each of them has a piece of information which assists us in delineating or describing a reservoir or monitoring the change (Walls et al, 2004).

By inversion, we convert seismic reflection amplitude to impedance profile (rock property information) and estimate model parameters (in term of impedance instead of reflectivity). Using inversion process, we try to “reduce discrepancies between observed and modeled seismic data” (Russell, 1988). The main objective here is to extract underlying geology and reservoir properties from some set of observed seismic data to use for better lithology and fluid prediction and prospect delineation (Russell, 1999). That is to say, the purpose is to obtain reliable estimate of P-wave velocity, S-wave velocity and density to calculate the physical properties and the earth`s structure.

With more complex geological conditions and rise in cost of hydrocarbon explorations, the inversion technique has become more popular and is widely used in the seismic industry for exploration and development of existing field. Inversion technique is a useful tool to derive elastic properties such as P-impedance, bulk modulus, Poisson`s ratio and so forth, which largely control the seismic response. As a result the outcomes we obtain from seismic inversion make up better volumetric estimation (hydrocarbon anomalies are better predicted) than seismic attributes derived from band limited seismic data (Connolly, 1999).


1.3 Objective of the Study

In seismic inversion, the aim is to transform seismic reflection data, which are interface-based property, into a layer-based quantitative rock property, descriptive of the reservoir.

In this work, an acoustic and elastic impedance volumes were inverted from near and far angle stacks, respectively.

The objective was to underscore which of these volumes was more effective in litho-fluid delineation in a given well in the Niger Delta.


1.4 Significance of the Study

Seismic inversion enables the specialist to separate the seismic wavelet from the reflection series characterized by the geologic formations and results in an estimate of residual impedance for each layer. Post-stack inversion is one alternative to conventional velocity analysis that provides higher resolution by inverting for impedance from the reflection strength (Bell, 2002).

Inversion replaces the seismic signature by a blocky response, corresponding to acoustic and/or elastic impedance layering. It facilitates the interpretation of meaningful geological and petro- physical boundaries in the subsurface. Inversion increases the resolution of conventional seismic in many cases and puts the study of reservoir parameters at a different level. It results in optimized volumetric, improved ranking of leads/prospects, better delineation of drainage areas and identification of ‘sweet spots’ in field development studies.

The ability to estimate acoustic impedance and a parameter related to shear impedance increases the interpreter’s ability to discriminate between different lithologies and fluid phases, resulting in a detailed reservoir characterization for improved hydrocarbon recovery.


1.5 Scope of Study / Limitation

The scope of this project is confined to the comparison of acoustic and elastic impedance inversion for rock property prediction. This exercise is not trivial, however, because the post- stack inversion technique ignores the fact that offset-dependent behavior (amplitude vs. offset) is buried in the stacked response and can cause significant perturbation of the results. One way to overcome this limitation and also boost resolution of the results at the same time is to use only the near-offset traces for the analysis. This is a good method to use because it provides higher resolution results due to the removal of far-offset data that are degraded by normal move-out (NMO) stretch.

One of the challenges of inversion is that the method does not normally include a low-frequency trend for velocity, but instead predicts variations in residual impedance that must be separated into velocity and density trends using well log data. Incorporating a low-frequency velocity trend in the analysis is possible, but it is commonly observed that the low-frequency trend, where combined with the residual impedances on the seismic data, does not match the predicted impedances from well logs. Thus, the calibration of this method still remains a limitation in many cases.

Seismic inversion is not a unique process. There are several acoustic impedance earth models that generate similar synthetic traces when convolved with the wavelet. The number of possible solutions is significantly reduced by putting constraints on the modelling and, in doing so, a most plausible scenario is retained. The support of other investigation techniques, like AVO analysis and forward modelling, increases the confidence in the inversion results. Seismic inversion depends heavily on the proper integration of well data. Seismic inversion is gradually becoming a routine processing step in field development studies as well as for exploration purposes. Even time lapse inversions are now conducted. The positive track record of case histories clearly demonstrates the added value of this type of seismic analysis (Curia D, 2009).


1.6 Study Area

Data used for this study were obtained from XY field, located in Niger Delta offshore, several kilometers south of Port Harcourt. The Niger Delta is one of the world’s largest and sandiest basins, situated on the West African continental margin at the apex of the Gulf of Guinea. It lies between latitudes 400N and 600N and longitudes 300E and 900E, and covers a surface area of approximately 75,000 sq. km. Figure 1 below shows the location of the area.


Chapter five


Conclusion and Recommendation

5.1 Conclusion

In this study, an effort has been made to compare acoustic and elastic impedance volumes with regards to litho-fluid discrimination in an offshore field in the Niger Delta. Difference of elastic impedance with time lapse seismic survey can provide better visualization in comparison to acoustic impedance as elastic impedance is more sensitive to fluid.

The seismic inversion volume provide very useful lithology information. Correlation with the well logs improves accuracy and identifies facies change at the large distance from the well location. The accuracy of the impedance logs depends upon the amplitude scaling and high and low frequency information. The proper selection of wavelet is also very important. Apart from this, good quality well logs data with correct elevation is required to make the synthetic seismic trace, particularly in the reservoir zone.

Model-based seismic inversion proved to be a useful method to understand the subsurface lithology. A key element of this study is that post stack impedance inversion provides a tool for better understanding and characterization of reservoir, giving a more accurate result which can lead to a reduction in risking the successful development of field and well placement.


5.2 Recommendation

Using the pre-stack seismic data, an inversion model at zero offset can be built. The obtained results can be compared with the results from post-stack seismic inversion using elastic impedance model with zero offset. This will give a clear picture that is it possible to use full- stack data to make the elastic impedance model or there is certain problem in initial model building for post-stack seismic inversion.

An integration of inversion results with AVO and other attributes to improve interpretation accuracy and get more valuable results for reservoir modeling and characterization. The results can be integrated with additional rock physics information in the area to further improve quality of the results, especially in areas far away from well control.


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FAQ On “Seismic Inversion: Comparison Of Acoustic And Elastic Impedance Inversion Models For Rock Property Prediction”


What is seismic inversion?

  • Seismic inversion is a technique used in geophysics to estimate the rock properties and subsurface structures by analyzing seismic data. It involves the transformation of seismic amplitude data into a quantitative representation of subsurface properties, such as acoustic impedance, elastic impedance, or porosity.

What is acoustic impedance inversion?

  • Acoustic impedance inversion is a type of seismic inversion that focuses on estimating the acoustic impedance of subsurface rocks. Acoustic impedance is the product of rock density and seismic wave velocity and is an important property for characterizing subsurface formations.

What is elastic impedance inversion?

  • Elastic impedance inversion is another type of seismic inversion that goes beyond acoustic impedance and also incorporates information about the elastic properties of rocks. Elastic impedance considers both compressional (P-wave) and shear (S-wave) wave velocities, as well as density, to provide a more comprehensive characterization of subsurface formations.

Why is rock property prediction important in seismic inversion?

A: Rock property prediction is essential in seismic inversion because it helps in understanding the composition, lithology, and fluid content of subsurface formations. By accurately estimating rock properties, such as porosity, permeability, and lithology, geoscientists can make better decisions related to reservoir characterization, hydrocarbon exploration, and production optimization.


What are the advantages of acoustic impedance inversion?

  • Acoustic impedance inversion has several advantages. It is relatively simpler and computationally less expensive compared to elastic impedance inversion. Acoustic impedance inversion also provides useful information about lithology and fluid content, allowing for reservoir characterization and identification of hydrocarbon-bearing zones.

What are the advantages of elastic impedance inversion?

  • Elastic impedance inversion offers additional benefits compared to acoustic impedance inversion. By incorporating both compressional and shear wave velocities, elastic impedance inversion provides more accurate estimates of rock properties, particularly in complex geological settings. It improves the differentiation between lithologies and enhances the prediction of reservoir quality and fluid saturation.

What are the limitations of acoustic impedance inversion?

  • Acoustic impedance inversion has some limitations. It assumes that the subsurface rocks are purely elastic, which may not always be the case. This can result in inaccurate estimates, especially in the presence of significant rock heterogeneity or fluid effects. Acoustic impedance inversion also does not account for shear wave information, limiting its ability to characterize certain rock types accurately.

What are the limitations of elastic impedance inversion?

  • Elastic impedance inversion also has some limitations. It requires additional seismic data, such as shear wave data, which may not always be available or of high quality. Elastic impedance inversion is computationally more intensive and complex compared to acoustic impedance inversion, requiring sophisticated algorithms and workflows. Moreover, errors in the estimation of shear wave velocities can propagate into the inversion results and affect the accuracy of the predictions.

Which inversion model is better for rock property prediction?

  • The choice between acoustic and elastic impedance inversion models depends on the specific geological context, data availability, and objectives of the study. Acoustic impedance inversion is often a good starting point due to its simplicity and computational efficiency. If the geological setting is complex or requires a more detailed characterization, elastic impedance inversion may provide more accurate results. It is common to compare and evaluate the results from both models to assess the strengths and limitations of each approach.

How are the inversion models validated?

  • Inversion models are typically validated by comparing the predicted rock properties with well-log data or core measurements from the subsurface. This involves quantifying the accuracy of the inversion results by calculating statistical metrics, such as correlation coefficients, root mean square errors, or crossplots. Additionally, geological knowledge and interpretation play a crucial role in the validation process to ensure the inversion results make geological sense and are consistent with other available information.

What are some applications of seismic inversion in the oil and gas industry?

  • Seismic inversion has various applications in the oil and gas industry. It is used for reservoir characterization, including estimating reservoir properties like porosity, permeability, and fluid content. Seismic inversion aids in hydrocarbon exploration by identifying potential traps and mapping subsurface structures. It also helps in well planning and field development by providing valuable insights into reservoir connectivity and heterogeneity. Additionally, seismic inversion plays a role in production optimization and monitoring of reservoirs over time.
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