S.P. Maurya

Banaras Hindu University | BHU · Department of Geophysics

A comprehensive evaluation of pore fluid properties, involves detailed analysis of various characteristics and behaviours relevant to its storage and management in subsurface reservoirs. The assessment includes variations in CO2 density, bulk modulus, temperature, pressure, velocities, and interactions with reservoir fluids and rocks. The seismic r...

Seismic inversion is a geophysical method that converts seismic reflection data into a quantitative representation of a reservoir's geological properties. These parameters are crucial for predicting reservoir rocks and the fluids present in the subsurface. Seismic inversion has been categorized into two ways: post-stack and pre-stack inversion. Pre...

This research delves into the utilization of Principal Component Analysis (PCA) and Probabilistic Neural Network (PNN) techniques for predicting porosity values based on seismic inversion data, which provides crucial insights into subsurface properties essential for reservoir characterization. The study integrates Principal Component Analysis (PCA)...

Seismic inversion, a crucial process in reservoir characterization, gains prominence in overcoming challenges associated with traditional methods, particularly in exploring deeper reservoirs. In this present study, we propose an inversion approach based on modern techniques like sparse layer reflectivity and particle swarm optimization to obtain in...

To estimate acoustic impedance and porosity in inter-well regions, a seismic inversion based on Hooke and Jeeves’ methods has been developed. The Hooke and Jeeves algorithm is a local optimization method that can reach a local or global optimum solution depending on the starting model. To prevent convergence to a local optimum, in the present study...

Accurate reservoir characterization is a crucial step for developing, managing, and optimizing hydrocarbon production. In this current study, we employ particle swarm optimization techniques (PSO) to perform an inversion of post-stack seismic data, extracting information about subsurface acoustic impedance and porosity. Conventional seismic inversi...

Accurate reservoir characterization is necessary to effectively monitor, manage, and increase production. A seismic inversion methodology using a genetic algorithm (GA) and particle swarm optimization (PSO) technique is proposed in this study to characterize the reservoir both qualitatively and quantitatively. It is usually difficult and expensive...

Porosity and acoustic impedance are important in the study of subsurface properties of rocks and soil. Porosity is influenced by the type of minerals, and fluids, and their distribution within the subsurface material. Acoustic impedance is a key parameter in seismic inversion because it governs the reflection and transmission of seismic waves at in...

Several strong to great earthquakes occurred in northeast India, indicating that the region is seismically very active. For a better understanding of the complex nature of tectonics in the Eastern Himalaya, a frequency-dependent attenuation relation based on coda waves is developed. The backscattering model of Aki and Chouet (J. Geophys. Res. 80: 3...

Seismic inversion is a computational technique used in geophysics to infer the properties of subsurface geological formations by analyzing seismic data. In order to lower the concentration of CO2 in the atmosphere, as a part of carbon capture and sequestration operation, these inversion techniques are essential for detecting CO2 leaks injected unde...

The dimension and size of data is growing rapidly with the extensive applications of computer science and lab based engineering in daily life. Due to availability of vagueness, later uncertainty, redundancy, irrelevancy, and noise, which imposes concerns in building effective learning models. Fuzzy rough set and its extensions have been applied to...

In the current study, a seismic inversion based on a hybrid optimisation of genetic algorithm (GA) and pattern search (PS) is carried out. The GA is an approach to global optimisation technique that always converges to the global optimum solution but takes much time to converge. On the other hand, the PS is a local optimisation technique and can co...

This article provides a comprehensive analysis of CO2 injection monitoring in the Sleipner Field. Ensuring the safe storage and containment of CO2 in geological formations or assigned storage sites, especially in the carbon capture and storage (CCS) projects. In this study, a seismic inversion method incorporating linear programming sparse spike in...

In this study, the focus is on predicting the properties of rocks beneath the Earth’s surface using global optimisation techniques such as genetic algorithms (GA), simulated annealing (SA) and particle swarm optimisation (PSO). The goal is to minimise the difference (error) between actual seismic data and synthetic (computed) seismic traces. Global...

In this study, acoustic impedance (P-impedance) distribution in the subsurface of the F3 block, Netherlands is determined using the linear programming (l1-norm) sparse spike inversion (LPSSI) method. The objectives of the study are to characterize the sand channel and extract high-resolution subsurface rock features from the low-resolution seismic...

Understanding subterranean reservoirs, geological characteristics, fluid composition, and hydrocarbon potential strongly relies on precise reservoir characterization. Seismic inversion is a key method in reservoir characterization to approximate the acoustic impedance and porosity of underlying rock formations using seismic and well-log data. A spa...

The continual collision and convergence of two plates, the Indian and the Eurasian plates, of extensively different crustal thicknesses, created one of the most dynamic geological provinces in the northern part of the Indian subcontinent, the Indo-Gangetic foreland basin (IGFB). The crustal geometry in this part of the Indian plate has remained the...

Seismic inversion, complemented by machine learning algorithms, significantly improves the accuracy and efficiency of subsurface parameter estimation from seismic data. In this comprehensive study, a comparative analysis of machine learning techniques is conducted to predict subsurface parameters within the inter-well region. The objective involves...

We statistically analyzed the fmax-model, κ-model and stress drop (Δσ) using surface and borehole data of the KIK-NET Japan seismological network. The statistical tests show no contribution of source in the fmax-model and κ-model. The ‘fmax’ values obtained in the present study are 4.2–11.0 Hz and 5–11.0 Hz for surface and borehole data, respective...

In this study, Rfpy software is utilized to compute the receiver functions to map Moho in the Northern Chile region. To obtain the teleseismic waveforms within an epicentral distance of 30° to 90°, the Package makes use of the IRIS station database. The receiver functions over stations AC04 and AC05 indicate a low-velocity layer possible area at a...

The 2012 Sumatra (Mw 8.6) earthquake, which falls into the largest and rarest group of the great intraplate earthquakes, continues to awe many brilliant minds. An enormous aftershock (Mw 8.2) was felt two hours after the Indian Ocean earthquake along the triple intersection of the Indian, Australian, and Sunda plates in the northwest. Over the past...

In the current study, a frequency-dependent attenuation relationship based on coda waves is developed for the Ecuador region. The single backscattering model developed by Aki and Chouet (J Geophys Res 80:3322–3342, 1975) is used to investigate the dependence of Coda-Q on lapse time frames. The waveforms of 49 local earthquakes recorded by a one-sta...

The present study provides a retrospective analysis of the geographical and chronological fluctuations of three basic statistical characteristics of seismicity using a big dataset of events that occurred between 1940 and 2022 in the Philippine region. For determining the spatial-time changes in a-value (seismic activity), b-value (recurrence graph...

One of the main challenges in reservoir characterization is the accurate prediction of lithology and saturation heterogeneities. In this study, a methodology has been developed that combines Monte Carlo simulation (MCS) and rock physics modelling (RPM) to explore subsurface properties and characterize reservoirs of the Krishna-Godavari (KG) Basin,...

This research paper introduces a comparative case study on reservoir characterization through seismic inversion techniques. The study specifically explores sparse layer reflectivity and a hybrid approach involving genetic algorithms and pattern search. The research assesses the effectiveness of these methodologies in delineating subsurface properti...

The critical task of overseeing and validating the storage and confinement of carbon dioxide (CO 2 ) in geological formations or designated repositories, particularly within the framework of carbon capture and storage (CCS) initiatives, involves the meticulous process of CO 2 sequestration monitoring. In this study, a seismic inversion method incor...

To estimate petrophysical parameters, seismic inversion techniques have been frequently used for estimating attributes like P-impedance, elastic impedance, S-impedance, density, Vp / Vs ratio, and gamma-ray logs from seismic and well-log data. These characteristics enable us to comprehend subsurface lithology for geo-seismic analysis, including its...

Accurate reservoir characterization is necessary to effectively monitor, manage, and increase production. A seismic inversion methodology using a genetic algorithm (GA) and particle swarm optimization (PSO) technique has been devised in thisstudy to characterize the reservoir both qualitatively and quantitatively. It has always been difficult and e...

In this study, seismic inversion is carried out using a genetic algorithm (GA) as well as a hybrid genetic algorithm (HGA) approach to optimize the objective function designed for the inversion. An HGA is a two steps coupled process, where a local optimization algorithm is applied to the best model obtained from each generation of the GA. The study...

Seismic 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 lo...

Seismic 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 lo...

ESOPA-GUI, a MATLAB-based graphical user interface software, is presented in this study. The ESOPA-GUI estimates the seismic spectrum source parameters using Brune’s model (1970). The software uses two high-frequency decay models to represent the high-frequency decay of an event’s acceleration and displacement spectra: fmax-model and κ-model. The B...

This chapter describes the application of Probabilistic Neural Network (PNN) for prediction of petrophysical parameters in the inter well region using post-stack 3D seismic and well log data of F3 block, the Netherland. The PNN analyses the number of attributes among themselves and the best combination of attributes is selected. Further, these attr...

The seismic body wave attenuation (Qα-1 and Qβ-1) characteristics of crust of the Kyushu region, Japan, has been investigated using the data of KIK-Net network of Japan. The frequency dependence relationships of Qα-1 and Qβ-1 have been computed using the extended coda wave normalization approach in the frequency range of 1.0 Hz to 24 Hz. Assessed a...

In the present study, seismic and well log information is incorporated with a multi-layer feed-forward neural network (MLFN) to predict porosity in the inter-well region. The aim of this study is to estimate a relationship between porosity and impedance to characterize the reservoir, if any, in the offshore F3 block, the Netherlands. MLFN is used t...

Seismic inversion methods are routinely used to estimate attributes such as P-impedance, S-impedance, density, P-wave and S-wave velocity, and elastic impedances from seismic and well log data. These attributes help to understand subsurface lithology and fluid content. There are several types of seismic inversion methods available in which model-ba...

The acoustic impedance estimation is very significant for characterizing the reservoir. This work aims to use and compare the results of two generic seismic post-stack inversion methods for characterizing the reservoir. These methods are Band-limited inversion (BLI) and Colored inversion (CI). By combining well log and band-limited seismic data, th...

In this chapter, the details of Amplitude variation with offset has been discussed. The method utilizes CMP gathers to produce AVO attribute which is used as good indicators of the presence of gas formation. The chapter is divided into two parts, in the first part it discusses about fluid replacement modeling and in the second section, it discusses...

Pre-stack seismic inversion utilizes as name suggest pre-stack seismic data along with well log data to estimate P-impedance, S-impedance, density and \({\text{V}}_{\text{P}} /{\text{V}}_{\text{S}}\) ratio away from the borehole. Pre-stack seismic inversion methods provides very high resolution subsurface images. This method provide more detail inf...

The optimization method is a process of getting the maximum or minimum of the inverse problem. This concept is used in this chapter to find the solution to the geophysical problems. Nowadays these techniques are used frequently in the exploration field to estimate subsurface information using seismic and well log data. Although these methods are us...

Seismic inversion methods in geophysics is a technique used to transform seismic reflection data into quantitative subsurface rock properties. It is methods to integrate seismic reflection data along with well log data to extract a variety of petrophysical parameters. Geophysicists regularly perform seismic surveys to collect subsurface geological...

Geostatistical inversion methods are routinely used to predict various geophysical parameters away from the boreholes using seismic and well log data. The geostatistics derives a surface using the values from the measured locations to estimate data points for each location in between the data points. The present chapter discusses different types of...

Post-stack seismic inversion utilizes post-stack seismic data along with well log data to estimate acoustic impedance. Post-stack seismic inversion is very fast compared to other pre-stack seismic inversion methods and provides a high-resolution subsurface image. This chapter discusses several types of post-stack seismic inversion methods namely mo...

Seismic data interpretation is a very crucial step and hence needs special care to the data. If some ambiguity will remain in the data, the interpretation will be false and hence loss of time and money. This chapter describes some of the processing steps of the seismic data that is necessary before proceeding towards the interpretation of seismic d...

The aim of the present study is to estimate the performance of seismic inversion methods for noise-free as well as noisy (gaussian) data. Seismic signal always contains unwanted signals, which mislead seismic data interpretation and hence their effects need to be understood. Many popular seismic inversion methods i.e. simultaneous inversion (SI), b...

This book introduces readers to seismic inversion methods and their application to both synthetic and real seismic data sets. Seismic inversion methods are routinely used to estimate attributes like P-impedance, S-impedance, density, the ratio of P-wave and S-wave velocities and elastic impedances from seismic and well log data. These attributes he...

Maximum likelihood sparse spike inversion (MLSSI) method is commonly used in the seismic industry to estimate petrophysical parameters in inter-well region. In present study, maximum likelihood sparse spike inversion technique is applied to the processed 3D post-stack seismic data from the F-3 block, the Netherlands, for estimation of acoustic impe...

Estimation of petrophysical parameters from seismic reflection data is one of the most crucial processes in the exploration of hydrocarbons. Thus, having sufficient information such as the lithology and fluid distribution of a reservoir is vital. With the application of Simultaneous seismic inversion, we will be able to improve the prediction of th...

The prime objective of this study is to find the suitable petrophysical parameters which depict maximum change in seismic amplitude due to fluid substitution. Therefore, in the present study the petrophysical parameters are analyzed to detect most sensitive parameters due to fluid substitution. The analysis is performed in three steps; In first ste...

In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model bas...

The present research describes a 1D inversion scheme for interpretation of large loop TEM data acquired using offset loop configuration due to a large loop source, over the layered earth models. The inversion is based on a non-linear least square method that generates a smooth layered earth model by minimizing the residual misfit function in an ite...

Seismic inversion involves extracting qualitative as well as quantitative information from seismic reflection data that can be analyzed in order to enhance geological and geophysical interpretation which is more subtle in a traditional seismic data interpretation. Among many approaches that have been made to improve interpretation of Post-stack sei...

In paper, a seismic inversion based on Genetic Algorithm (GA) is performed to characterize the reservoir using seismic data only from the Blackfoot field, Alberta, Canada. The algorithm is first tested on synthetically generated data to optimize the Genetic algorithm parameters. The error analysis between the inverted and expected results suggested...

In the present study, elastic impedance (EI) inversion is performed to estimate subsurface elastic properties in the inter well region. These elastic properties are helpful to discriminate gas bearing formation from gas free formation, as well as, overpressure zone. For the analysis, seismic reflection data from the Penobscot Scotia shelf, Canada i...

Simulate Annealing is a global optimization algorithm used to find global optima in the presence of large numbers of local optima. Pre-stack seismic inversion is performed based on simulate annealing for the data from the Penobscot field; Nova Scotia, Canada in this study and a verity of attributes are estimated. These attributes are P-wave velocit...

In the present study, pre- and post-stack seismic inversions are performed to estimate subsurface petrophysical properties from the seismic reflection data, obtained over the Penobscot field, Canada. Such methods are routinely used to estimate subsurface property from seismic reflection data but the problem arises in deciding which method will prov...

In present study, Linear Programming (l1 - norm) sparse spike inversion (LPSSI) technique is used to estimate acoustic impedance distribution in the subsurface of the Blackfoot field, Alberta Canada. The aim of study is to derive high resolution subsurface rock property from the low resolution seismic data and characterize clastic Glauconitic chann...

Sparse-Spike inversion techniques are used to estimate distribution of acoustic impedance in inter well region, the important parameters for characterizing the reservoir facies from seismic and well log data. The purpose of sparse spike impedance inversion is to obtain high-resolution impedance profile of the subsurface from the low resolution seis...

The acoustic impedance (AI) inversion aims to obtain a high-resolution impedance volume by integrating well-log and band-limited seismic data. Two AI inversion schemes the colored inversion (CI) and the model-based inversion (MBI) are utilized to characterize possible sand channel from the post-stack seismic section and log data from 13 wells from...

The Transient electromagnetic method (TEM) represents a class of electromagnetic (EM) methods, which are relatively new and are widely being used for ground water, environmental and geotechnical problems. The present work describes a forward computation and an inversion schemes for the interpretation of large loop transient electromagnetic (TEM) da...

The general expression of TEM response of large loop source over the layered earth models is not available in the literature for arbitrary source-receiver positions, except for the case of central loop and coincident loop configurations over the homogeneous earth model. In the present study, an attempt is made to present the TEM response of a large...

A genetic algorithm based seismic inversion of data from the Blackfoot field, Alberta, Canada is presented in this study. The effectiveness of genetic algorithm is tested in the absence of any well control. Initially, the algorithm is tested with synthetically generated data. The error analysis between the expected and inverted results pointed out...

Seismic colored inversion is a post stack inversion techniques which transform seismic data into layered rock properties. Seismic colored inversion performs significantly better than traditional inversion methods like model based inversion, band-limited inversion methods (Lancaster et al., 2000). Other inversion methods are time consuming, expensiv...

Time lapse seismic reservoir modeling can image fluid flow effects in a reservoir if the changes in seismic pattern can be observed. In the present study, Gassmann fluid substitution analysis and forward modeling based on subsurface model has been carried out to predict reservoir response. 2D seismic modeling was performed to simulate the CO2 injec...

The CO2 storage potential of a shallow sandstone layer of the Blackfoot, Alberta, Canada is evaluated in this study. Seismic reservoir monitoring can image fluid-flow effects in a reservoir if the changes in petrophysical parameters of the reservoir due to production or on-going recovery processes are large enough to detect. In order to assess the...

Rock physics models play a crucial role in seismic reservoir characterization studies. Gassmann’s (1951) equations commonly are used to predict velocity changes resulting from different pore fluid saturations. However, the input parameters are often crudely estimated, and the resulting estimates of fluid effects can be unrealistic (Batzle et. al, 1...

Inversion of seismic data for estimating elastic properties of the subsurface has been routinely applied for seismic exploration studies. Non-linearity and non-uniqueness together with intensive forward modeling procedures make the problem challenging to solve. Pre-stack seismic waveform inversion also sometimes referred to as Simultaneous Inversio...