Risk Reduction on the Western Siberia Prospect Using Stochastic Seismic Inversion and Geological Constraints

2021 ◽  
Author(s):  
Anton Khitrenko ◽  
Sergey Fedotkin ◽  
Ayk Nazaryan ◽  
Svetlana Zhigulskiy ◽  
Pavel Emelyanov
Keyword(s):  
Seismic Data ◽  
Western Siberia ◽  
Reservoir Characterization ◽  
Probability Model ◽  
Seismic Inversion ◽  
Advantages And Disadvantages ◽  
Fluid Properties ◽  
Geological Constraints ◽  
Stochastic Seismic Inversion ◽  
Source Of Information

Abstract Seismic data is a main source of information for lateral forecast of lithofacies. No one can deny that seismic data is a useful method to determinate structure of prospects. However, we have to accept to urgent need to implement steps that will make possible to predict distribution of lithofacies. In exploration, the prediction of lithology and fluid properties is a main goal. Popularity and comparative simplicity of inversion, made seismic inversion popular for reservoir characterization. Despite the benefits of method, inability to estimate uncertainty of models, stochastic seismic inversion was inveted. A stochastic seismic inversion combine relationship with varying lithofacies parameters and elastic properties using uncertainty of each data. Additional modification of stochastic seismic inversion is geological constraints allows to exclude not appropriate realization and obtain correct probability model of lithofacies. Comparison of approaches and results on a real set provided from the Tyumen formation in Western Siberia allows to estimate advantages and disadvantages of modification stochastic Seismic inversion.

Applications of quantitative prestack seismic analysis to unconventional resource play characterization in the Permian/Delaware Basin

2019 ◽  
Vol 38 (2) ◽  
pp. 106-115 ◽  
Author(s):  
Phuong Hoang ◽  
Arcangelo Sena ◽  
Benjamin Lascaud
Keyword(s):  
Hydraulic Fracturing ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Seismic Analysis ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Yield Attributes ◽  
Horizontal Drilling ◽  
Delaware Basin ◽  
Unconventional Resource

The characterization of shale plays involves an understanding of tectonic history, geologic settings, reservoir properties, and the in-situ stresses of the potential producing zones in the subsurface. The associated hydrocarbons are generally recovered by horizontal drilling and hydraulic fracturing. Historically, seismic data have been used mainly for structural interpretation of the shale reservoirs. A primary benefit of surface seismic has been the ability to locate and avoid drilling into shallow carbonate karsting zones, salt structures, and basement-related major faults which adversely affect the ability to drill and complete the well effectively. More recent advances in prestack seismic data analysis yield attributes that appear to be correlated to formation lithology, rock strength, and stress fields. From these, we may infer preferential drilling locations or sweet spots. Knowledge and proper utilization of these attributes may prove valuable in the optimization of drilling and completion activities. In recent years, geophysical data have played an increasing role in supporting well planning, hydraulic fracturing, well stacking, and spacing. We have implemented an integrated workflow combining prestack seismic inversion and multiattribute analysis, microseismic data, well-log data, and geologic modeling to demonstrate key applications of quantitative seismic analysis utilized in developing ConocoPhillips' acreage in the Delaware Basin located in Texas. These applications range from reservoir characterization to well planning/execution, stacking/spacing optimization, and saltwater disposal. We show that multidisciplinary technology integration is the key for success in unconventional play exploration and development.

High-resolution reservoir characterization by an acoustic impedance inversion of a Tertiary deltaic clinoform system in the North Sea

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. O57-O67 ◽  
Author(s):  
Daria Tetyukhina ◽  
Lucas J. van Vliet ◽  
Stefan M. Luthi ◽  
Kees Wapenaar
Keyword(s):  
North Sea ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Structural Information ◽  
Sampling Rate ◽  
Seismic Inversion ◽  
Acoustic Properties ◽  
The North ◽  
The North Sea ◽  
Well Data

Fluvio-deltaic sedimentary systems are of great interest for explorationists because they can form prolific hydrocarbon plays. However, they are also among the most complex and heterogeneous ones encountered in the subsurface, and potential reservoir units are often close to or below seismic resolution. For seismic inversion, it is therefore important to integrate the seismic data with higher resolution constraints obtained from well logs, whereby not only the acoustic properties are used but also the detailed layering characteristics. We have applied two inversion approaches for poststack, time-migrated seismic data to a clinoform sequence in the North Sea. Both methods are recursive trace-based techniques that use well data as a priori constraints but differ in the way they incorporate structural information. One method uses a discrete layer model from the well that is propagated laterally along the clinoform layers, which are modeled as sigmoids. The second method uses a constant sampling rate from the well data and uses horizontal and vertical regularization parameters for lateral propagation. The first method has a low level of parameterization embedded in a geologic framework and is computationally fast. The second method has a much higher degree of parameterization but is flexible enough to detect deviations in the geologic settings of the reservoir; however, there is no explicit geologic significance and the method is computationally much less efficient. Forward seismic modeling of the two inversion results indicates a good match of both methods with the actual seismic data.

Accuracy of wavelets, seismic inversion, and thin-bed resolution

2017 ◽  
Vol 5 (4) ◽  
pp. T523-T530
Author(s):  
Ehsan Zabihi Naeini ◽  
Mark Sams
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Frequency Content ◽  
Frequency Model ◽  
North West ◽  
The North ◽  
Well Data

Broadband reprocessed seismic data from the North West Shelf of Australia were inverted using wavelets estimated with a conventional approach. The inversion method applied was a facies-based inversion, in which the low-frequency model is a product of the inversion process itself, constrained by facies-dependent input trends, the resultant facies distribution, and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness. The bandwidth of the seismic data is approximately 5–70 Hz, and the well data used to extract the wavelet used in the inversion are only 400 ms long. As such, there was little control on the lowest frequencies of the wavelet. Different wavelets were subsequently estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low-frequency seismic. The revised inversion showed greater gas-sand continuity and an extension of the reservoir at one flank. Noise-free synthetic examples indicate that thin-bed delineation can depend on the accuracy of the low-frequency content of the wavelets used for inversion. Underestimation of the low-frequency contents can result in missing thin beds, whereas underestimation of high frequencies can introduce false thin beds. Therefore, it is very important to correctly capture the full frequency content of the seismic data in terms of the amplitude and phase spectra of the estimated wavelets, which subsequently leads to a more accurate thin-bed reservoir characterization through inversion.

scholarly journals Seismic Interpretation and Inversion Leading to an Accurate Reservoir Characterization in a Carbonate Environment

2021 ◽  
Vol 2 (12) ◽  
pp. 1229-1230
Author(s):  
Yasir Bashir ◽  
Nordiana Mohd Muztaza ◽  
Nur Azwin Ismail ◽  
Ismail Ahmad Abir ◽  
Andy Anderson Bery ◽  
...  
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Seismic Interpretation ◽  
And Inversion

Seismic data acquired in the field show the subsurface reflectors or horizon among the geological strata, while the seismic inversion converts this reflector information into the acoustic impedance section which shows the layer properties based on lithology. The research aims to predict the porosity to identify the reservoir which is in between the tight layer. So, the output of the seismic inversion is much more batter than the seismic as it is closer to reality such as geology. Seismic inversion is frequently used to determine rock physics properties, for example, acoustic impedance and porosity.

Fluids and lithofacies prediction based on integration of well-log data and seismic inversion: a machine learning approach

Geophysics ◽  
2021 ◽  
pp. 1-67
Author(s):  
Luanxiao Zhao ◽  
Caifeng Zou ◽  
Yuanyuan Chen ◽  
Wenlong Shen ◽  
Yirong Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Seismic Data ◽  
Domain Knowledge ◽  
Reservoir Characterization ◽  
Model Building ◽  
Imbalanced Data ◽  
Seismic Inversion ◽  
Well Log ◽  
Spatial Constraints ◽  
Imbalanced Data Sets

Seismic prediction of fluid and lithofacies distributions is of great interest to reservoir characterization, geological model building, and flow unit delineation. Inferring fluids and lithofacies from seismic data under the framework of machine learning is commonly subject to issues of limited features, imbalanced data sets, and spatial constraints. As a consequence, an XGBoost based workflow, which takes feature engineering, data balancing, and spatial constraints into account, is proposed to predict the fluid and lithofacies distribution by integrating well-log and seismic data. The constructed feature set based on simple mathematical operations and domain knowledge outperforms the benchmark group consisting of conventional elastic attributes of P-impedance and Vp/Vs ratio. A radial basis function characterizing the weights of training samples according to the distances from the available wells to the target region is developed to impose spatial constraints on the model training process, significantly improving the prediction accuracy and reliability of gas sandstone. The strategy combining the synthetic minority oversampling technique (SMOTE) and spatial constraints further increases the F1 score of gas sandstone and also benefits the overall prediction performance of all the facies. The application of the combined strategy on prestack seismic inversion results generates a more geologically reasonable spatial distribution of fluids, thus verifying the robustness and effectiveness of the proposed workflow.

Prestack waveform inversion of three-dimensional seismic data — An example from the Rock Springs Uplift, Wyoming, USA

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. B1-B12 ◽  
Author(s):  
Josiane Pafeng ◽  
Subhashis Mallick ◽  
Hema Sharma
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Waveform Inversion ◽  
Three Dimensional ◽  
Seismic Inversion ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Seismic Waveform ◽  
Rock Springs Uplift ◽  
Rock Springs

Applying seismic inversion to estimate subsurface elastic earth properties for reservoir characterization is a challenge in exploration seismology. In recent years, waveform-based seismic inversions have gained popularity, but due to high computational costs, their applications are limited, and amplitude-variation-with-offset/angle inversion is still the current state-of-the-art. We have developed a genetic-algorithm-based prestack seismic waveform inversion methodology. By parallelizing at multiple levels and assuming a locally 1D structure such that forward computation of wave equation synthetics is computationally efficient, this method is capable of inverting 3D prestack seismic data on parallel computers. Applying this inversion to a real prestack seismic data volume from the Rock Springs Uplift (RSU) located in Wyoming, USA, we determined that our method is capable of inverting the data in a reasonable runtime and producing much higher quality results than amplitude-variation-with-offset/angle inversion. Because the primary purpose for seismic data acquisition at the RSU was to characterize the subsurface for potential targets for carbon dioxide sequestration, we also identified and analyzed some potential primary and secondary storage formations and their associated sealing lithologies from our inversion results.

Depth-domain seismic reflectivity inversion with compressed sensing technique

2017 ◽  
Vol 5 (1) ◽  
pp. T1-T9 ◽  
Author(s):  
Rui Zhang ◽  
Kui Zhang ◽  
Jude E. Alekhue
Keyword(s):  
Compressed Sensing ◽  
Time Domain ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Synthetic Data ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Depth Migration ◽  
Band Limited ◽  
The Time Domain

More and more seismic surveys produce 3D seismic images in the depth domain by using prestack depth migration methods, which can present a direct subsurface structure in the depth domain rather than in the time domain. This leads to the increasing need for applications of seismic inversion on the depth-imaged seismic data for reservoir characterization. To address this issue, we have developed a depth-domain seismic inversion method by using the compressed sensing technique with output of reflectivity and band-limited impedance without conversion to the time domain. The formulations of the seismic inversion in the depth domain are similar to time-domain methods, but they implement all the elements in depth domain, for example, a depth-domain seismic well tie. The developed method was first tested on synthetic data, showing great improvement of the resolution on inverted reflectivity. We later applied the method on a depth-migrated field data with well-log data validated, showing a great fit between them and also improved resolution on the inversion results, which demonstrates the feasibility and reliability of the proposed method on depth-domain seismic data.

Integrated reservoir characterization of a Utica Shale field

2018 ◽  
Vol 37 (9) ◽  
pp. 656-661
Author(s):  
Jinming Zhu
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Water Saturation ◽  
Clay Content ◽  
Seismic Inversion ◽  
Data Set ◽  
Utica Shale ◽  
Multidisciplinary Study ◽  
3D Seismic Data

We performed an integrated multidisciplinary study for reservoir characterization of a Utica Shale field in eastern Ohio covered by a multiclient 3D seismic data set acquired in 2015. Elastic seismic inversion was performed in-house for effective reservoir characterization of the Utica Shale, which covers the interval from the top of Upper Utica (UUTIC) to the top of Trenton Limestone. Accurate, high-fidelity inversion results were obtained, including acoustic impedance, shear impedance, density, and VP/VS. These consistent inversion results allow for the reliable calculation of geomechanical and petrophysical properties of the reservoir. The inverted density clearly divides the Point Pleasant (PPLS) interval as low density from the overlying UUTIC Shale interval. Both Poisson's ratio (PR) and brittleness unmistakably separate the underlying PPLS from the overlying Utica interval. The PPLS Formation is easier to hydraulically fracture due to its much lower PR. Sequence S4 is the best due to its higher Young's modulus to sustain the open fractures. The calculated petrophysical volumes indisputably delineate the traditional Utica Shale into two distinctive sections. The upper section, the UUTIC, can be described as having 1%–2% total organic carbon (TOC), 3.5%–4.8% porosity, 10%–24% water saturation, and 40%–58% clay content. The lower section, PPLS, can be described as having 3%–4.5% TOC, 5%–9% porosity, 2%–10% water saturation, and about 15%–35% clay content. Both sections exhibit spatial variation of the properties. Nevertheless, the underlying PPLS is obviously a significantly better reservoir and operationally easier to produce.

scholarly journals Poisson impedance for lithology characterization

2021 ◽  
Vol 6 (1) ◽  
pp. 23-28
Author(s):  
A. V. Khitrenko ◽  
K. A. Groman ◽  
A. V. Lobusev
Keyword(s):  
Elastic Properties ◽  
Seismic Data ◽  
Western Siberia ◽  
Oil And Gas ◽  
Seismic Attributes ◽  
Seismic Inversion ◽  
Seismic Survey ◽  
Lateral Heterogeneity ◽  
Main Method

Tyumen formation is a formation with very considerably lateral heterogeneity. It influences on process of exploration oil and gas traps. No one can deny that seismic survey is a main method for prediction lateral heterogeneity. Nowadays, geoscientists can model different useful seismic attributes, apart from structural maps. Seismic inversion is most effective tool for transformation amplitude seismic data into elastic properties. However, sometimes result of seismic inversion is very hard to understand and analyze. In this work, authors will show additional methods for better understanding results of seismic inversion using Impedance Poisson. Area of research is located in the Western Siberia.

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