scholarly journals Application of maximum likelihood and model-based seismic inversion techniques: a case study from K-G basin, India

2021 ◽  
Author(s):  
Richa ◽  
S. P. Maurya ◽  
Kumar H. Singh ◽  
Raghav Singh ◽  
Rohtash Kumar ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Gamma Ray ◽  
Seismic Inversion ◽  
Reservoir Rock ◽  
Well Log ◽  
Log Data ◽  
Petrophysical Parameters ◽  
Model Based

AbstractSeismic inversion is a geophysical technique used to estimate subsurface rock properties from seismic reflection data. Seismic data has band-limited nature and contains generally 10–80 Hz frequency hence seismic inversion combines well log information along with seismic data to extract high-resolution subsurface acoustic impedance which contains low as well as high frequencies. This rock property is used to extract qualitative as well as quantitative information of subsurface that can be analyzed to enhance geological as well as geophysical interpretation. The interpretations of extracted properties are more meaningful and provide more detailed information of the subsurface as compared to the traditional seismic data interpretation. The present study focused on the analysis of well log data as well as seismic data of the KG basin to find the prospective zone. Petrophysical parameters such as effective porosity, water saturation, hydrocarbon saturation, and several other parameters were calculated using the available well log data. Low Gamma-ray value, high resistivity, and cross-over between neutron and density logs indicated the presence of gas-bearing zones in the KG basin. Three main hydrocarbon-bearing zones are identified with an average Gamma-ray value of 50 API units at the depth range of (1918–1960 m), 58 API units (2116–2136 m), and 66 API units (2221–2245 m). The average resistivity is found to be 17 Ohm-m, 10 Ohm-m, and 12 Ohm-m and average porosity is 15%, 15%, and 14% of zone 1, zone 2, and zone 3 respectively. The analysis of petrophysical parameters and different cross-plots showed that the reservoir rock is of sandstone with shale as a seal rock. On the other hand, two types of seismic inversion namely Maximum Likelihood and Model-based seismic inversion are used to estimate subsurface acoustic impedance. The inverted section is interpreted as two anomalous zones with very low impedance ranging from 1800 m/s*g/cc to 6000 m/s*g/cc which is quite low and indicates the presence of loose formation.

Mapping lithofacies and pore‐fluid probabilities in a North Sea reservoir: Seismic inversions and statistical rock physics

Geophysics ◽  
2001 ◽  
Vol 66 (4) ◽  
pp. 988-1001 ◽  
Author(s):  
T. Mukerji ◽  
A. Jørstad ◽  
P. Avseth ◽  
G. Mavko ◽  
J. R. Granli
Keyword(s):  
North Sea ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Probability Distributions ◽  
Rock Physics ◽  
Normal Incidence ◽  
Seismic Inversion ◽  
Training Data ◽  
Well Log ◽  
Statistical Rock Physics

Reliably predicting lithologic and saturation heterogeneities is one of the key problems in reservoir characterization. In this study, we show how statistical rock physics techniques combined with seismic information can be used to classify reservoir lithologies and pore fluids. One of the innovations was to use a seismic impedance attribute (related to the [Formula: see text] ratio) that incorporates far‐offset data, but at the same time can be practically obtained using normal incidence inversion algorithms. The methods were applied to a North Sea turbidite system. We incorporated well log measurements with calibration from core data to estimate the near‐offset and far‐offset reflectivity and impedance attributes. Multivariate probability distributions were estimated from the data to identify the attribute clusters and their separability for different facies and fluid saturations. A training data was set up using Monte Carlo simulations based on the well log—derived probability distributions. Fluid substitution by Gassmann’s equation was used to extend the training data, thus accounting for pore fluid conditions not encountered in the well. Seismic inversion of near‐offset and far‐offset stacks gave us two 3‐D cubes of impedance attributes in the interwell region. The near‐offset stack approximates a zero‐offset section, giving an estimate of the normal incidence acoustic impedance. The far offset stack gives an estimate of a [Formula: see text]‐related elastic impedance attribute that is equivalent to the acoustic impedance for non‐normal incidence. These impedance attributes obtained from seismic inversion were then used with the training probability distribution functions to predict the probability of occurrence of the different lithofacies in the interwell region. Statistical classification techniques, as well as geostatistical indicator simulations were applied on the 3‐D seismic data cube. A Markov‐Bayes technique was used to update the probabilities obtained from the seismic data by taking into account the spatial correlation as estimated from the facies indicator variograms. The final results are spatial 3‐D maps of not only the most likely facies and pore fluids, but also their occurrence probabilities. A key ingredient in this study was the exploitation of physically based seismic‐to‐reservoir property transforms optimally combined with statistical techniques.

Geostatistical seismic inversion for frontier exploration

2017 ◽  
Vol 5 (4) ◽  
pp. T477-T485 ◽  
Author(s):  
Ângela Pereira ◽  
Rúben Nunes ◽  
Leonardo Azevedo ◽  
Luís Guerreiro ◽  
Amílcar Soares
Keyword(s):  
Acoustic Impedance ◽  
Seismic Reflection ◽  
Seismic Inversion ◽  
Well Log ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Log Data ◽  
The Real ◽  
Reflection Data ◽  
Impedance Models

Numerical 3D high-resolution models of subsurface petroelastic properties are key tools for exploration and production stages. Stochastic seismic inversion techniques are often used to infer the spatial distribution of the properties of interest by integrating simultaneously seismic reflection and well-log data also allowing accessing the spatial uncertainty of the retrieved models. In frontier exploration areas, the available data set is often composed exclusively of seismic reflection data due to the lack of drilled wells and are therefore of high uncertainty. In these cases, subsurface models are usually retrieved by deterministic seismic inversion methodologies based exclusively on the existing seismic reflection data and an a priori elastic model. The resulting models are smooth representations of the real complex geology and do not allow assessing the uncertainty. To overcome these limitations, we have developed a geostatistical framework that allows inverting seismic reflection data without the need of experimental data (i.e., well-log data) within the inversion area. This iterative geostatistical seismic inversion methodology simultaneously integrates the available seismic reflection data and information from geologic analogs (nearby wells and/or analog fields) allowing retrieving acoustic impedance models. The model parameter space is perturbed by a stochastic sequential simulation methodology that handles the nonstationary probability distribution function. Convergence from iteration to iteration is ensured by a genetic algorithm driven by the trace-by-trace mismatch between real and synthetic seismic reflection data. The method was successfully applied to a frontier basin offshore southwest Europe, where no well has been drilled yet. Geologic information about the expected impedance distribution was retrieved from nearby wells and integrated within the inversion procedure. The resulting acoustic impedance models are geologically consistent with the available information and data, and the match between the inverted and the real seismic data ranges from 85% to 90% in some regions.

scholarly journals The Use of Well-Log Data in the Geomechanical Characterization of Middle Cambrian Tight Sandstone Formation: A Case Study from Eastern Pomerania, Poland

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6022
Author(s):  
Małgorzata Słota-Valim ◽  
Anita Lis-Śledziona
Keyword(s):  
Seismic Data ◽  
Reservoir Rock ◽  
Rock Properties ◽  
Hydraulic Fractures ◽  
Well Log ◽  
Tight Sandstone ◽  
Middle Cambrian ◽  
Log Data ◽  
Geomechanical Characterization

Geomechanical characterization plays a key role in optimizing the stimulation treatment of tight reservoir formations. Petrophysical models help classify the reservoir rock as the conventional or unconventional type and determine hydrocarbon-saturated zones. Geomechanical and petrophysical models are fundamentally based on well-log data that provide reliable and high-resolution information, and are used to determine various relationships between measured borehole parameters and modeled physical rock properties in 3D space, with the support of seismic data. This paper presents the geomechanical characterization of the Middle Cambrian (Cm2) sediments from Eastern Pomerania, north Poland. To achieve the aim of this study, 1D well-log-based and 3D models based on seismic data of the rocks’ petrophysical, elastic, and strength properties, as well as numerical methods, were used. The analysis of the Middle Cambrian deposits revealed vertical and horizontal heterogeneity in brittleness, the direction of horizontal stresses, and the fracturing pressure required to initiate hydraulic fractures. The most prone to fracturing is the gas-saturated tight sandstones belonging to the Paradoxides Paradoxissimus formation of Cm2, exhibiting the highest brittleness and highest fracturing pressure necessary to stimulate this unconventional reservoir formation.

Lithology and fluid prediction from seismic data and well log data

1993 ◽  
Author(s):  
A. W. H. Bunch ◽  
P. W. Dromgoole
Keyword(s):  
Seismic Data ◽  
Well Log ◽  
Log Data

THE INTEGRATED USE OF PETROPHYSICAL, AVO, SEISMIC INVERSION AND 3D VISUALISATION TOOLS FOR RESERVOIR CHARACTERISATION

2001 ◽  
Vol 41 (2) ◽  
pp. 131
Author(s):  
A.G. Sena ◽  
T.M. Smith
Keyword(s):  
Seismic Data ◽  
New Technology ◽  
Seismic Inversion ◽  
Well Log ◽  
Reservoir Properties ◽  
Gas Field ◽  
Geological Interpretation ◽  
3D Visualisation ◽  
Quantitative Understanding ◽  
Inversion Techniques

The successful exploration for new reservoirs in mature areas, as well as the optimal development of existing fields, requires the integration of unconventional geological and geophysical techniques. In particular, the calibration of 3D seismic data to well log information is crucial to obtain a quantitative understanding of reservoir properties. The advent of new technology for prestack seismic data analysis and 3D visualisation has resulted in improved fluid and lithology predictions prior to expensive drilling. Increased reservoir resolution has been achieved by combining seismic inversion with AVO analysis to minimise exploration risk.In this paper we present an integrated and systematic approach to prospect evaluation in an oil/gas field. We will show how petrophysical analysis of well log data can be used as a feasibility tool to determine the fluid and lithology discrimination capabilities of AVO and inversion techniques. Then, a description of effective AVO and prestack inversion tools for reservoir property quantification will be discussed. Finally, the incorporation of the geological interpretation and the use of 3D visualisation will be presented as a key integration tool for the discovery of new plays.

Colored and linear inversions to relative acoustic impedance

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. N15-N27 ◽  
Author(s):  
Carlos A. M. Assis ◽  
Henrique B. Santos ◽  
Jörg Schleicher
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Computational Cost ◽  
Synthetic Data ◽  
Seismic Source ◽  
Alternative Methods ◽  
Well Log ◽  
Linear Inversion ◽  
Amplitude Inversion ◽  
Band Limited

Acoustic impedance (AI) is a widely used seismic attribute in stratigraphic interpretation. Because of the frequency-band-limited nature of seismic data, seismic amplitude inversion cannot determine AI itself, but it can only provide an estimate of its variations, the relative AI (RAI). We have revisited and compared two alternative methods to transform stacked seismic data into RAI. One is colored inversion (CI), which requires well-log information, and the other is linear inversion (LI), which requires knowledge of the seismic source wavelet. We start by formulating the two approaches in a theoretically comparable manner. This allows us to conclude that both procedures are theoretically equivalent. We proceed to check whether the use of the CI results as the initial solution for LI can improve the RAI estimation. In our experiments, combining CI and LI cannot provide superior RAI results to those produced by each approach applied individually. Then, we analyze the LI performance with two distinct solvers for the associated linear system. Moreover, we investigate the sensitivity of both methods regarding the frequency content present in synthetic data. The numerical tests using the Marmousi2 model demonstrate that the CI and LI techniques can provide an RAI estimate of similar accuracy. A field-data example confirms the analysis using synthetic-data experiments. Our investigations confirm the theoretical and practical similarities of CI and LI regardless of the numerical strategy used in LI. An important result of our tests is that an increase in the low-frequency gap in the data leads to slightly deteriorated CI quality. In this case, LI required more iterations for the conjugate-gradient least-squares solver, but the final results were not much affected. Both methodologies provided interesting RAI profiles compared with well-log data, at low computational cost and with a simple parameterization.

Integration of uncertain well-log data into geostatistical seismic inversion

2016 ◽  
Author(s):  
Pedro Pereira ◽  
Fernando Bordignon ◽  
Ruben Nunes ◽  
Leonardo Azevedo ◽  
Amilcar Soares
Keyword(s):  
Seismic Inversion ◽  
Well Log ◽  
Log Data

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.

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