Inversion Of Seismic Data Research Articles

Decimetric-resolution stochastic inversion of shallow marine seismic reflection data: dedicated strategy and application to a geohazard case study

Characterisation of the top 10-50 m of the subseabed is key for landslide hazard assessment, offshore structure engineering design and underground gas-storage monitoring. In this paper, we present a methodology for the stochastic inversion of ultra-high-frequency (UHF, 0.2-4.0 kHz) pre-stack seismic reflection waveforms, designed to obtain a decimetric-resolution re- mote elastic characterisation of the shallow sediments with minimal pre-processing and lit- tle a-priori information. We use a genetic algorithm in which the space of possible solutions is sampled by explicitly decoupling the short and long wavelengths of the P-wave velocity model. This approach, combined with an objective function robust to cycle skipping, outperforms a conventional model parametrisation when the ground-truth is offset from the centre of the search domain. The robust P-wave velocity model is used to precondition the width of the search range of the multi-parameter elastic inversion, thereby improving the efficiency in high dimensional parametrizations. Multiple independent runs provide a set of independent results from which the reproducibility of the solution can be estimated. In a real dataset acquired in Finneidfjord, Norway, we also demonstrate the sensitivity of UHF seismic inversion to shallow subseabed anomalies that play a role in submarine slope stability. Thus, the methodology has the potential to become an important practical tool for marine ground model building in spatially heterogeneous areas, reducing the reliance on expensive and time-consuming coring campaigns for geohazard mitigation in marine areas.

Joint Inversion of Seismic and Audio Magnetotelluric Data with Structural Constraint for Metallic Deposit

Audio magnetotelluric (AMT) and seismic methods are widely used to detect metallic deposits. However, each geophysical method only provides partial information of the underground target. Besides, individual methods have inherent limitations and ambiguity which leads to non-uniqueness when solving the inverse problem. To obtain a more robust and consistent ore deposit model, it is best to integrate different geophysical methods and data types. Towards this effort, we propose a joint inversion algorithm using cross-gradient constraint to build a connection between seismic and AMT data, and simultaneously invert for a resistivity and P-wave velocity model. Compared with separate AMT Gauss–Newton inversion and seismic Full waveform inversion (FWI) method, we can get more detailed and robust inversion results. In addition, frequency domain FWI with the Limited-Memory-Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm provides an effective way to reduce computer memory usage and improve convergence speed. This joint inversion algorithm has been tested using simple synthetic models with two cross targets. The results obtained with separate inversions were compared with those obtained with joint inversion. Then, we applied the algorithm to geophysical models of the Jinchuan sulfide deposit. The AMT results obtained with joint inversion of seismic data were better than those obtained with separate AMT inversion. The joint inversion approach appears more robust than the traditional separate FWI inversion and it is recommended that the proposed algorithm be considered in future projects of real field data.

Geophysical pre‐investigation for a Stockholm tunnel project: joint inversion and interpretation of geoelectric and seismic refraction data in an urban environment

ABSTRACTUnderground constructions for public traffic purposes are becoming increasingly important for urban areas in order to use the limited space more efficiently. Several electric resistivity tomography and seismic refraction tomography measurements were performed crossing a water passage near Stockholm during the pre‐investigation phase of a tunnel building project. The objective was to determine the bedrock interface and qualitatively assess the rock quality. The scope of this study is to present a field case in an urban environment and show improvements of geophysical results due to additional model constraints by a joint inversion. Results of individual inversions show a large transition zone below the seabed from electric resistivity tomography. Some parts of the seismic refraction tomography have a low model resolution, due to gas‐bearing sediments with a low velocity together with a high noise level, which leads to insufficient investigation depth that makes it difficult to determine the bedrock interface. However, the bedrock interface could be reconstructed in the resistivity model by performing a joint inversion, using the seismic velocity model to constrain the electric resistivity tomography model and vice versa. Adjacent geotechnical soundings support the joint inversion results. A vertical low resistive zone could be identified as a dominant fracture zone in the southern part of the investigated area. In general, the joint inversion approach significantly improved the electric resistivity tomography results and provided a more reliable bedrock estimation.

Calculation of organic matter volume (TOC) based on genetic inversion of seismic data

Calculation of organic matter volume (TOC) based on genetic inversion of seismic data

A new petrophysical joint inversion workflow: Advancing on reservoir’s characterization challenges

Reservoir characterization objectives are to understand the reservoir rocks and fluids through accurate measurements to help asset teams develop optimal production decisions. Within this framework, we develop a new workflow to perform petrophysical joint inversion (PJI) of seismic and controlled-source electromagnetic (CSEM) data to resolve for reservoirs properties. Our workflow uses the complementary information contained in seismic, CSEM, and well-log data to improve the reservoir’s description drastically. The advent of CSEM, measuring resistivity, brought the possibility of integrating multiphysics data within the characterization workflow, and it has the potential to significantly enhance the accuracy at which reservoir properties and saturation, in particular, can be determined. We determine the power of PJI in the retrieval of reservoir parameters through a case study, based on a deepwater oil field offshore Brazil in the Sergipe-Alagoas Basin, to augment the certainty with which reservoir lithology and fluid properties are constrained.

Joint inversion of multi-component seismic data: application to Bakken petroleum exploration and development

Abstract The Reservoir Characterization Project (RCP) at Colorado School of Mines acquired the rights to a 9C, 3D seismic survey in Mountrail County, North Dakota with specific focus on how multi-component seismic data could aid in exploration and development of the Bakken Shale (Figure 1). Proximity to the giant Parshall Field made the survey particularly attractive as operators in the Bakken wanted to find if additional value could be created by acquiring multi-component seismic data in this major unconventional resource play.

Elastic full-waveform inversion of vertical seismic profile data acquired with distributed acoustic sensors

Distributed acoustic sensing (DAS) is a rapidly developing technology particularly useful for the acquisition of vertical seismic profile (VSP) surveys. DAS data are increasingly used for seismic imaging, but not for estimating rock properties. We have developed a workflow for estimating elastic properties of the subsurface using full-waveform inversion (FWI) of DAS VSP data. Whereas conventional borehole geophones usually measure three components of particle velocity, DAS measures a single quantity, which is an approximation of the strain or strain rate along the fiber. Standard FWI algorithms are developed for particle velocity data, and hence their application to DAS data requires conversion of these data to particle velocity along the fiber. This conversion can be accomplished by a specially designed filter. Field measurements show that the conversion result is close to vertical particle velocity as measured by geophones. Elastic time-domain FWI of a synthetic multioffset VSP data set for a vertical well shows that the inversion of the vertical component alone is sufficient to recover elastic properties of the subsurface. Application of the proposed workflow to a multioffset DAS data set acquired at the CO2CRC Otway Project site in Victoria, Australia, reveals salient subhorizontal layering consistent with the known geology of the site. The inverted [Formula: see text] model at the well location matches the upscaled [Formula: see text] log with a correlation coefficient of 0.85.

Constrained nonlinear amplitude variation with offset inversion using Zoeppritz equations

The inversion of prestack seismic data using amplitude variation with offset (AVO) has received increased attention in the past few decades because of its key role in estimating reservoir properties. AVO is mainly governed by the Zoeppritz equations, but traditional inversion techniques are based on various linear or quasilinear approximations to these nonlinear equations. We have developed an efficient algorithm for nonlinear AVO inversion of precritical reflections using the exact Zoeppritz equations in multichannel and multi-interface form for simultaneous estimation of the P-wave velocity, S-wave velocity, and density. The total variation constraint is used to overcome the ill-posedness while solving the forward nonlinear model and to preserve the sharpness of the interfaces in the parameter space. The optimization is based on a combination of Levenberg’s algorithm and the split Bregman iterative scheme, in which we have to refine the data and model parameters at each iteration. We refine the data via the original nonlinear equations, but we use the traditional cost-effective linearized AVO inversion to construct the Jacobian matrix and update the model. Numerical experiments show that this new iterative procedure is convergent and converges to a solution of the nonlinear problem. We determine the performance and optimality of our nonlinear inversion algorithm with various simulated and field seismic data sets.

Joint facies and reservoir properties inversion

I have developed a joint inversion of seismic data for the simultaneous estimation of facies and reservoir properties, such as porosity, mineralogy, and saturation. The inversion method is a Bayesian approach for the joint estimation of facies and reservoir rock/fluid properties based on the statistical assumption of mixtures of nonparametric distributions of the model parameters. A mixture distribution is a convex combination of distributions. In the approach, I use a mixture of [Formula: see text] nonparametric distributions, where [Formula: see text] is the number of facies, and the weights of the combination represent the probability of the facies. The statistical assumptions in the proposed Bayesian inversion allow modeling multimodal and nonsymmetric distributions of the model parameters because they are not restricted to specific shapes of the probability distributions and allow modeling multimodal distributions caused by the presence of different facies and nonlinear relations between reservoir properties and elastic data. The inversion can be applied to elastic properties from well logs or derived from seismic data, and they can be combined with traditional Bayesian linearized AVO inversion. The method provides the point-by-point posterior distribution of facies and reservoir properties, as well as the most-likely models and its associated uncertainty, and it is successfully applied to real data.

Detection of Tectonically Deformed Coal Using Model-Based Joint Inversion of Multi-Component Seismic Data

Tectonically-deformed coal (TDC) is a potential source of threats to coal-mining safety. Finding out the development and distribution of TDCs is a difficult task in coalfield seismic explorations. Based on the previous investigations, the P- to S-wave velocity ratio (α/β) is a stable parameter for the identification of TDCs and most TDCs have α/β values of less than 1.7. Here, a TDC detection method using a model-based joint inversion of the multi-component seismic data is proposed. Following the least square theories, the amplitude variation with offset gathers of the PP- and PS-waves are jointly inverted into the corresponding α/β values. The prior models generated from the P- and S-wave velocity and density logs are employed in the joint inversion to enhance the inversed models. Model test results show that the model-based inversion is of high anti-noise ability and has a good recognition ability of TDCs. The proposed method is applied to a work area of the Guqiao mine in China. The TDCs developed in coal seam 13-1 are effectively identified according to their inverted α/β values of less than 1.7. The detection result is verified by the well and tunnel excavation information.

Crustal Footprint of the Hainan Plume Beneath Southeast China

AbstractAlthough global and regional seismic tomography results have revealed the presence of a mantle plume beneath Hainan Island, there is little evidence for a hotspot track associated with the Hainan plume. Here a joint inversion of satellite gravity measurements and seismic surface wave dispersion data was performed, and the results show that a linear corridor of high seismic velocity anomalies beneath the crust is located northeast of Hainan Island beneath the Southeast China. Geodynamic modeling further demonstrates that this corridor could have been formed by the interactions between a mantle plume and the continental lithosphere with a weak lower crust. Volcanic age distributions of sporadic oceanic island basalts suggest that this track was likely formed since the late Cretaceous, which helps to constrain the averaged plate velocity of the South China Block, relative to the Hainan plume, to be ~1.8 cm/year to the northeast since 80 Ma. Our result provides a novel explanation for the crustal thickness variations, related Vs anomalies, and observed oceanic island basalts in this area. It also provides an independent way for constraining plate motion history of the continental lithosphere.

Spark-based intelligent parameter inversion method for prestack seismic data

Seismic exploration is an oil exploration method by utilizing seismic information. Useful reservoir parameter information can be gained through inversion of seismic information to effectively carry out exploration work. Prestack data are characterized by large data size and rich information. Rich reservoir parameter information can be obtained through inversion of prestack data. Due to mass prestack seismic data, existing single computer environment cannot satisfy computation requirement of huge data size. Thus, an efficient and fast method is urgently needed to solve the inversion problem of prestack seismic big data. Since local optimum may be easily caught when genetic algorithm is used to optimize elastic parameters, the inversion effect is not obvious. In particular, the optimization effect for the density parameters is not good. An intelligent optimization algorithm is proposed in this paper for elastic parameter inversion of prestack seismic data. The algorithm improves genetic manipulation. The improved algorithm has been used for model trial for log data, and good inversion effect has been achieved. The inverted elastic parameters well fit with the log curve of the theoretical model. The improved algorithm effectively improves the inversion accuracy of density parameters. In this paper, the algorithm has been implemented on Spark model, and the results show that the parallel model can effectively reduce operation time of the algorithm.

Sub-basalt Imaging of Hydrocarbon-Bearing Mesozoic Sediments Using Ray-Trace Inversion of First-Arrival Seismic Data and Elastic Finite-Difference Full-Wave Modeling Along Sinor\u2013Valod Profile of Deccan Syneclise, India

Imaging below the basalt for hydrocarbon exploration is a global problem because of poor penetration and significant loss of seismic energy due to scattering, attenuation, absorption and mode-conversion when the seismic waves encounter a highly heterogeneous and rugose basalt layer. The conventional (short offset) seismic data acquisition, processing and modeling techniques adopted by the oil industry generally fails to image hydrocarbon-bearing sub-trappean Mesozoic sediments hidden below the basalt and is considered as a serious problem for hydrocarbon exploration in the world. To overcome this difficulty of sub-basalt imaging, we have generated dense synthetic seismic data with the help of elastic finite-difference full-wave modeling using staggered-grid scheme for the model derived from ray-trace inversion using sparse wide-angle seismic data acquired along Sinor–Valod profile in the Deccan Volcanic Province of India. The full-wave synthetic seismic data generated have been processed and imaged using conventional seismic data processing technique with Kirchhoff pre-stack time and depth migrations. The seismic image obtained correlates with all the structural features of the model obtained through ray-trace inversion of wide-angle seismic data, validating the effectiveness of robust elastic finite-difference full-wave modeling approach for imaging below thick basalts. Using the full-wave modeling also allows us to decipher small-scale heterogeneities imposed in the model as a measure of the rugose basalt interfaces, which could not be dealt with ray-trace inversion. Furthermore, we were able to accurately image thin low-velocity hydrocarbon-bearing Mesozoic sediments sandwiched between and hidden below two thick sequences of high-velocity basalt layers lying above the basement.

Seismic reservoir characterization of a class-1 amplitude variation with offset turbiditic system located offshore Cote d’Ivoire, West Africa

We have evaluated a case study, in which a class-1 amplitude variation with offset (AVO) turbiditic system located offshore Cote d’Ivoire, West Africa, is characterized in terms of rock properties (lithology, porosity, and fluid content) and stratigraphic elements using well-log and prestack seismic data. The methodology applied involves (1) the conditioning and modeling of well-log data to several plausible geologic scenarios at the prospect location, (2) the conditioning and inversion of prestack seismic data for P- and S-wave impedance estimation, and (3) the quantitative estimation of rock property volumes and their geologic interpretation. The approaches used for the quantitative interpretation of these rock properties were the multiattribute rotation scheme for lithology and porosity characterization and a Bayesian lithofluid facies classification (statistical rock physics) for a probabilistic evaluation of fluid content. The result indicates how the application and integration of these different AVO- and rock-physics-based reservoir characterization workflows help us to understand key geologic stratigraphic elements of the architecture of the turbidite system and its static petrophysical characteristics (e.g., lithology, porosity, and net sand thickness). Furthermore, we found out how to quantify and interpret the risk related to the probability of finding hydrocarbon in a class-1 AVO setting using seismically derived elastic attributes, which are characterized by having a small level of sensitivity to changes in fluid saturation.

Well log and seismic data analysis for complex pore-structure carbonate reservoir using 3D rock physics templates

The pore structure in heterogeneous carbonate rock is usually very complex. This complex pore system makes the relationship between the velocity and porosity of the rock highly scattered, so that for the classical two-dimensional rock physics template (2D RPT) it is not enough to accurately describe the quantitative relationship between the rock elastic parameters of this kind of reservoir and its porosity and water saturation. Therefore it is possible to attribute the effect of pore type to that of the porosity or water saturation, and leads to great deviations when applying such a 2D RPT to predict the porosity and water saturation in seismic reservoir prediction and hydrocarbon detection. This paper first presents a method to establish a new three-dimensional rock physics template (3D RPT) by integrating the Gassmann equations and the porous rock physics model, and use it to characterize the quantitative relation between rock elastic properties and the reservoir parameters including the pore aspect ratio, porosity and water saturation, and to predict these parameters from the known elastic properties. The test results on the real logging and seismic inversion data show that the 3D RPT can accurately describe the variations of elastic properties with the porosity, water saturation and pore-structure parameters, and effectively improve the accuracy of reservoir parameters prediction.

Multiscale phase inversion of seismic data

We present a scheme for multiscale phase inversion (MPI) of seismic data that is less sensitive than full-waveform inversion (FWI) to the unmodeled physics of wave propagation and to a poor starting model. To avoid cycle skipping, the multiscale strategy temporally integrates the traces several times, i.e., high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, lower frequencies in the data are boosted by using integrated traces of lower order as the input data. The input data are also filtered into different narrow frequency bands for the MPI implementation. Numerical results with synthetic acoustic data indicate that, for the Marmousi model, MPI is more robust than conventional multiscale FWI when the initial model is moderately far from the true model. Results from synthetic viscoacoustic and elastic data indicate that MPI is less sensitive than FWI to some of the unmodeled physics. Inversion of marine data indicates that MPI is more robust and produces modestly more accurate results than FWI for this data set.

Crustal heat production and estimate of terrestrial heat flow in central East Antarctica, with implications for thermal input to the East Antarctic ice sheet

Abstract. Terrestrial heat flow is a critical first-order factor governing the thermal condition and, therefore, mechanical stability of Antarctic ice sheets, yet heat flow across Antarctica is poorly known. Previous estimates of terrestrial heat flow in East Antarctica come from inversion of seismic and magnetic geophysical data, by modeling temperature profiles in ice boreholes, and by calculation from heat production values reported for exposed bedrock. Although accurate estimates of surface heat flow are important as an input parameter for ice-sheet growth and stability models, there are no direct measurements of terrestrial heat flow in East Antarctica coupled to either subglacial sediment or bedrock. As has been done with bedrock exposed along coastal margins and in rare inland outcrops, valuable estimates of heat flow in central East Antarctica can be extrapolated from heat production determined by the geochemical composition of glacial rock clasts eroded from the continental interior. In this study, U, Th, and K concentrations in a suite of Proterozoic (1.2–2.0 Ga) granitoids sourced within the Byrd and Nimrod glacial drainages of central East Antarctica indicate average upper crustal heat production (Ho) of about 2.6 ± 1.9 µW m−3. Assuming typical mantle and lower crustal heat flux for stable continental shields, and a length scale for the distribution of heat production in the upper crust, the heat production values determined for individual samples yield estimates of surface heat flow (qo) ranging from 33 to 84 mW m−2 and an average of 48.0 ± 13.6 mW m−2. Estimates of heat production obtained for this suite of glacially sourced granitoids therefore indicate that the interior of the East Antarctic ice sheet is underlain in part by Proterozoic continental lithosphere with an average surface heat flow, providing constraints on both geodynamic history and ice-sheet stability. The ages and geothermal characteristics of the granites indicate that crust in central East Antarctica resembles that in the Proterozoic Arunta and Tennant Creek inliers of Australia but is dissimilar to other areas like the Central Australian Heat Flow Province that are characterized by anomalously high heat flow. Age variation within the sample suite indicates that central East Antarctic lithosphere is heterogeneous, yet the average heat production and heat flow of four age subgroups cluster around the group mean, indicating minor variation in the thermal contribution to the overlying ice sheet from upper crustal heat production. Despite these minor differences, ice-sheet models may favor a geologically realistic input of crustal heat flow represented by the distribution of ages and geothermal characteristics found in these glacial clasts.

Joint inversion of seismic traveltime and frequency-domain airborne electromagnetic data for hydrocarbon exploration

Geophysical joint inversion requires the setting of a few parameters for optimum performance of the process. However, there are yet no known detailed procedures for selecting the various parameters for performing the joint inversion. Previous works on the joint inversion of electromagnetic (EM) and seismic data have reported parameter applications for data sets acquired from the same dimensional geometry (either in two dimensions or three dimensions) and few on variant geometry. But none has discussed the parameter selections for the joint inversion of methods from variant geometry (for example, a 2D seismic travel and pseudo-2D frequency-domain EM data). With the advantage of affordable computational cost and the sufficient approximation of a 1D EM model in a horizontally layered sedimentary environment, we are able to set optimum joint inversion parameters to perform structurally constrained joint 2D seismic traveltime and pseudo-2D EM data for hydrocarbon exploration. From the synthetic experiments, even in the presence of noise, we are able to prescribe the rules for optimum parameter setting for the joint inversion, including the choice of initial model and the cross-gradient weighting. We apply these rules on field data to reconstruct a more reliable subsurface velocity model than the one obtained by the traveltime inversions alone. We expect that this approach will be useful for performing joint inversion of the seismic traveltime and frequency-domain EM data for the production of hydrocarbon.

Blocky inversion of multichannel elastic impedance for elastic parameters

Petrophysical description of reservoirs requires proper knowledge of elastic parameters like P- and S-wave velocities (Vp and Vs) and density (ρ), which can be retrieved from pre-stack seismic data using the concept of elastic impedance (EI). We propose an inversion algorithm which recovers elastic parameters from pre-stack seismic data in two sequential steps. In the first step, using the multichannel blind seismic inversion method (exploited recently for recovering acoustic impedance from post-stack seismic data), high-resolution blocky EI models are obtained directly from partial angle-stacks. Using an efficient total-variation (TV) regularization, each angle-stack is inverted independently in a multichannel form without prior knowledge of the corresponding wavelet. The second step involves inversion of the resulting EI models for elastic parameters. Mathematically, under some assumptions, the EI's are linearly described by the elastic parameters in the logarithm domain. Thus a linear weighted least squares inversion is employed to perform this step. Accuracy of the concept of elastic impedance in predicting reflection coefficients at low and high angles of incidence is compared with that of exact Zoeppritz elastic impedance and the role of low frequency content in the problem is discussed. The performance of the proposed inversion method is tested using synthetic 2D data sets obtained from the Marmousi model and also 2D field data sets. The results confirm the efficiency and accuracy of the proposed method for inversion of pre-stack seismic data.

Time-lapse joint AVO inversion using generalized linear method based on exact Zoeppritz equations

The conventional method of time-lapse AVO (Amplitude Versus Offset) inversion is mainly based on the approximate expression of Zoeppritz equations. Though the approximate expression is concise and convenient to use, it has certain limitations. For example, its application condition is that the difference of elastic parameters between the upper medium and lower medium is little and the incident angle is small. In addition, the inversion of density is not stable. Therefore, we develop the method of time-lapse joint AVO inversion based on exact Zoeppritz equations. In this method, we apply exact Zoeppritz equations to calculate the reflection coefficient of PP wave. And in the construction of objective function for inversion, we use Taylor series expansion to linearize the inversion problem. Through the joint AVO inversion of seismic data in baseline survey and monitor survey, we can obtain the P-wave velocity, S-wave velocity, density in baseline survey and their time-lapse changes simultaneously. We can also estimate the oil saturation change according to inversion results. Compared with the time-lapse difference inversion, the joint inversion doesn't need certain assumptions and can estimate more parameters simultaneously. It has a better applicability. Meanwhile, by using the generalized linear method, the inversion is easily implemented and its calculation cost is small. We use the theoretical model to generate synthetic seismic records to test and analyze the influence of random noise. The results can prove the availability and anti-noise-interference ability of our method. We also apply the inversion to actual field data and prove the feasibility of our method in actual situation.