Simultaneous Inversion Research Articles

Downhole microseismic data interpretation for media anisotropy evaluation with limited acquisition geometry in Western Siberia

We have evaluated the results of processing and interpretation for one of the first projects in Russia for downhole microseismic monitoring of hydraulic fracturing in Western Siberia. The data are characterized by large distance to the acquisition array and noisy recordings. We illustrate that preliminary quality control of microseismic array installation is a useful tool that may predict some of the issues and help to promote better acquisition quality. Therefore, it is important to reiterate the significance of the supervision for microseismic field measurements, especially when the technology is tested in new regions. Despite limited acquisition aperture and a comparatively small number of observed microseismic events, it is possible to derive valuable interpretation results from the data set. The geometry of the event locations suggests significant unplanned development of the hydraulic fractures, including a significant shift of the fracture from the initiation point. Records with clear S-wave splitting allowed us to determine arrival times of P waves and two S waves for several microseismic events. Arrival times were then used for simultaneous kinematic inversion for microseismic-event location and anisotropic velocity-model update (layered transversely isotropic with the vertical axis of symmetry model). We estimate significant anisotropy from microseismic data. Thomsen parameters [Formula: see text] and [Formula: see text] are well constrained, whereas parameter [Formula: see text] is constrained only for one of the layers.

Three-dimensional time-lapse inversion of transient electromagnetic data, with application at an Icelandic geothermal site

SUMMARY Transient electromagnetic (TEM) is an efficient non-invasive method to map electrical conductivity distribution in the subsurface. This paper presents an inversion scheme for 3-D TEM time-lapse (TL) data using a generalized minimum support (MS) norm and its application to monitoring conductivity changes over time. In particular, two challenges for TL TEM applications are addressed: (i) the survey repetition with slightly different acquisition position, that is, because systems are not installed and (ii) non-optimal data coverage above the TL anomalies, for instance, due to the presence of infrastructure that limits the acquisition layout because of coupling. To address these issues, we developed a new TEM TL inversion scheme with the following features: (1) a multimesh approach for model definition and forward computations, which allows for seamless integration of data sets with different acquisition layouts; (2) 3-D sensitivity calculation during the inversion, which allows retrieving conductivity changes in-between TEM soundings and (3) simultaneous inversion of two data sets at once, imposing TL constraints defined in terms of a generalized MS norm, which ensures compact TL changes. We assess the relevance of our implementations through a synthetic example and a field example. In the synthetic example, we study the capability of the inversion scheme to retrieve compact time-lapse changes despite slight changes in the acquisition layout and the effect of data coverage on the retrieval of TL changes. Results from the synthetic tests are used for interpreting field data, which consists of two TEM data sets collected in 2019 and 2020 at the Nesjavellir high-temperature geothermal site (Iceland) within a monitoring project of H2S sequestration. Furthermore, the field example illustrates the effect of the trade-off between data misfit and TL constraints in the inversion objective function, using the tuning settings of the generalized MS norm. Based on the results from both the synthetic and field cases, we show that our implementation of 3-D TL inversion has a robust performance for TEM monitoring.

Tectonic Pattern Imaging of Southern Sumatra Region Using Double Difference Seismic Tomography

Southern Sumatra and its surroundings are close to the contact zone of the Indo-Australian plate and Eurasian plate, so the area always relates to the high seismicity zone. The Sumatran subduction zone, the Mentawai fault, and several segments of the Sumatran fault drive seismic activities in the area. Tectonic settings are essential to understanding the area's source and hazard. This understanding can be obtained using the relocated hypocenter distribution and the 3D velocity model in the area. Relocated hypocenters and velocity models are obtained from simultaneous inversion from the BMKG earthquake catalog in January 2012-December 2020 using the double difference seismic tomography method. Seismic velocity inversion of P- and S- wave tomograms image the thermal zone beneath Dempo and Patah volcanoes at a depth of 30-50 km. Slab dehydration is also observed in several forearc high zone. Both phenomena are associated with negative anomalies. The Sumatran and Mentawai fault zones are marked between negative and positive anomalies on the contact zone. The subducted slab of the Indo-Australian plate is observed until a depth of 150 km, which is the maximum depth of nodes used in this study. The granitic basement beneath Anak Krakatau volcano is detected until 10 km. Two of those geological features are related to positive anomalies.

Simultaneous inversion for surface wave phase velocity and earthquake centroid parameters: methodology and application

Simultaneous inversion for surface wave phase velocity and earthquake centroid parameters: methodology and application

Simultaneous inversion for surface wave phase velocity and earthquake centroid parameters: methodology and application

Simultaneous inversion for surface wave phase velocity and earthquake centroid parameters: methodology and application

Simultaneous inversion for surface wave phase velocity and earthquake centroid parameters: methodology and application

Simultaneous inversion for surface wave phase velocity and earthquake centroid parameters: methodology and application

Elastic Impedance Simultaneous Inversion for Multiple Partial Angle Stack Seismic Data with Joint Sparse Constraint

Elastic impedance (EI) inversion for partial angle stack seismic data is a key technology in seismic reservoir prediction within the oil and gas industry. EI inversion provides a consistent framework to invert partial angle stack seismic data, just as the AI inversion does for post-stack data. The commonly used EI inversion process is angle by angle. Hence, the inverted EI for different angles may be nonconforming, especially for the seismic data with a low signal-to-noise ratio. This paper proposes to simultaneously invert multiple partial angle stack seismic data to obtain EI for different angles at once. To obtain conformable EI, we used the joint sparse constraint on the reflection coefficients for different angles. Then, the objective function for simultaneous EI inversion was constructed. Next, synthetic seismic data profiles with three different angles were used to show the superiority of the proposed EI inversion method compared to the conventional method. At last, a real seismic data line was used to test the feasibility of the proposed method in practice. The inversion results of synthetic data and real data showed that it provides an effective new alternative method to estimate EI from partial stack seismic data.

Geometrically Induced Selectivity and Unidirectional Electroosmosis in Uncharged Nanopores.

Selectivity toward positive and negative ions in nanopores is often associated with electroosmotic flow, the control of which is pivotal in several micro-nanofluidic technologies. Selectivity is traditionally understood to be a consequence of surface charges that alter the ion distribution in the pore lumen. Here we present a purely geometrical mechanism to induce ionic selectivity and electroosmotic flow in uncharged nanopores, and we tested it via molecular dynamics simulations. Our approach exploits the accumulation of charges, driven by an external electric field, in a coaxial cavity that decorates the membrane close to the pore entrance. The selectivity was shown to depend on the applied voltage and becomes completely inverted when reversing the voltage. The simultaneous inversion of ionic selectivity and electric field direction causes a unidirectional electroosmotic flow. We developed a quantitatively accurate theoretical model for designing pore geometry to achieve the desired electroosmotic velocity. Finally, we show that unidirectional electroosmosis also occurs in much more complex scenarios, such as a biological pore whose structure presents a coaxial cavity surrounding the pore constriction as well as a complex surface charge pattern. The capability to induce ion selectivity without altering the pore lumen shape or the surface charge may be useful for a more flexible design of selective membranes.

Differential Rotation in Jupiter's Interior Revealed by Simultaneous Inversion for the Magnetic Field and Zonal Flux Velocity

AbstractA key objective of the current Juno mission (Bolton et al., 2017, https://doi.org/10.1126/science.aal2108) is the direct determination of the secular variation (time dependency) of Jupiter's internal magnetic field in order to further understand the dynamics of Jupiter's interior. Here, we find that the residuals to a static, baseline model of the magnetic field are consistent with the effects of secular variation, specifically secular variation arising from zonal drift of the field. We present a technique for simultaneously inverting for the main magnetic field and secular variation due to zonal drift of the field. We explore the required drift systematically and argue that although the drift is dominated by a prograde super‐rotation, corresponding to approximately 1 part in 106 relative to System IIIa (1965), there is also evidence for differential drift of the field. We compare the resultant secular variation with that determined by Moore et al. (2019, https://doi.org/10.1038/s41550-019-0772-5) and Connerney et al. (2022, https://doi.org/10.1029/2021je007055) and find good agreement. This suggests that the drift rate of Jupiter's magnetic field is steady over time periods of several decades, though short period secular variation (such as that resulting from torsional oscillations) superimposed on this steady secular variation is still possible.

A hybrid workflow for updating 1D velocity model and microseismic event location

An accurate velocity model is critical for determining the microseismic event locations. Simultaneous inversion and alternating inversion are two common strategies for updating the 1D velocity model and estimating event locations in downhole microseismic monitoring. Numerical experiments demonstrate that the limited distribution of the receivers and the coupling between the event locations and the 1D velocity model may lead to an ill-conditioned problem for simultaneous inversion. Thus, a good initial estimate is critical to producing a stable solution. Moreover, the alternating inversion decouples event locations from the velocity model, but it converges to the optimal solution very slowly. In this study, we present a hybrid workflow to update both the 1D velocity model and microseismic event locations by combining two strategies. We first acquire an initial solution with the alternating inversion and then conduct the simultaneous inversion with the alternating result as the starting values. Numerical tests and field data are applied to demonstrate the effectiveness of the hybrid workflow.

Simultaneous estimation of ocean mesoscale and coherent internal tide sea surface height signatures from the global altimetry record

Abstract. This study proposes an approach to estimate the ocean sea surface height signature of coherent internal tides from a 25-year along-track altimetry record, with a single inversion over time, resolving both internal tide contributions and mesoscale eddy variability. The inversion is performed on a reduced-order basis of topography and practically achieved with a conjugate gradient. The particularity of this approach is to mitigate the potential aliasing effects between mesoscales and internal tide estimation from the uneven altimetry sampling (observing the sum of these components) by accounting for their statistics simultaneously, while other methods generally use a prior mesoscale. The four major tidal components are considered (M2, K1, S2, O1) over the period 1992–2017 on a global configuration. From the solution, we use altimetry data after 2017 for independent validation in order to evaluate the performance of the simultaneous inversion and compare it with an existing model.

Panoptic View of Mantle Flow Beneath Trans‐Continental Northeast Asia: Distinct Variation Detected From ∼2,000 km Shear Wave Splitting Profile

AbstractWe obtained a panoptic view of the pattern of mantle flow in the “Big Mantle Wedge” associated with the stagnation of the subducting Pacific slab. We applied a simultaneous inversion of multiple waveforms method to measure SKS‐wave splitting parameters for a dense seismic array in trans‐continental Northeast Asia. We identify distinct patterns separated by the North‐South Gravity Lineament (NSGL): to the west, the ENE fast axis orientation with small δt reflects limited frozen anisotropy in the stable lithosphere; while to the east, local variation of anisotropy is superimposed on the NNW‐dominated fast direction, suggesting contribution of other mechanisms rather than the only asthenospheric flow. Within a distance of 200 km crossing the NSGL, we reveal a gradual clockwise rotation in the fast direction, and the keel‐deflected flow caused by the 60–80 km reduction in the lithosphere thickness across the NSGL might contribute to the variation of anisotropy.

Estimation of porosity from well logs and seismic using artificial neural network

The Artificial Neural Network (ANN) is widely used to map and estimate reservoir properties. Since ANN has the ability of non-linear computing and self-error correction, it serves as an alternative method to enhance reservoir characterization by improving reservoir properties' prediction. This study employed an integrated approach where seismic, and well log data are used alongside ANN to evaluate petrophysical properties in Field X, South Caspian Basin. The study field is situated in the South Caspian Basin, which developed during Tertiary-Quaternary. The South Caspian Basin covers the southern part of the Caspian Basin, coastal regions of eastern Azerbaijan, northern Iran, and western Turkmenistan. The field is geologically situated on an elongated and multi-crest, anticlinal feature, better known as Apsheron Sill. Available data set consists of log data from four wells: X1, X2, X3, X4, and 3D pre-stack seismic data. Firstly, the reservoir properties were calculated from the well log data. The simultaneous inversion was carried out to obtain elastic rock properties like the P-impedance, S-impedance, density. After that, elastic properties were used to obtain 3D dimensional SQp and SQs attributes. Furthermore, the Radial basis function Neural Network (RBFN) model was created with optional inputs: volume of P-impedance, S-impedance, density, SQp, SQs and property logs and outputs: porosity. Moreover, this research work demonstrates an application of SQp and SQs attributes for properties prediction using neural network. The neural network's primary purpose is to determine a relationship between obtained volumes and reservoir parameters, porosity at well locations. The RBFN model is successfully trained and validated on the field data. The results demonstrated an excellent correlation between actual property logs. They predicted properties, which gives confidence for spatial prediction in areas where well logs are not available.

Physics-Informed Deep Neural Network for Inhomogeneous Magnetized Plasma Parameter Inversion

Plasma parameter inversion is important for space plasma physics and applications, particularly for inhomogeneous magnetized plasmas. A physics-informed deep neural network for Maxwell’s plasma coupling system is proposed in this letter. The network architecture consists of inhomogeneous plasma parameter inversion and electromagnetic field reconstruction. We verified our physics-informed neural network method for one-dimensional (1-D) Maxwell’s plasma coupling system with inhomogeneous magnetized plasma parameters. The simulation results show that this meshless method can effectively achieve simultaneous inversion of inhomogeneous plasma parameter and global field based on sparse sampling. The physics-informed deep neural network for Maxwell’s plasma coupling system has a certain generalization ability, which may be applied for more complex plasma applications.

A Carbonate Reservoir Prediction Method Based on Deep Learning and Multiparameter Joint Inversion

Deep-water carbonate reservoirs are currently the focus of global oil and gas production activities. The characterization of strongly heterogeneous carbonate reservoirs, especially the prediction of fluids in deep-water presalt carbonate reservoirs, exposes difficulties in reservoir inversion due to their complex structures and weak seismic signals. Therefore, a multiparameter joint inversion method is proposed to comprehensively utilize the information of different seismic angle gathers and the simultaneous inversion of multiple seismic parameters. Compared with the commonly used simultaneous constrained sparse-pulse inversion method, the multiparameter joint inversion method can characterize thinner layers that are consistent with data and can obtain higher-resolution presalt reservoir results. Based on the results of multiparameter joint inversion, in this paper, we further integrate the long short-term memory network algorithm to predict the porosity of presalt reef reservoirs. Compared with a fully connected neural network based on the backpropagation algorithm, the porosity results are in better agreement with the new log porosity curves, with the average porosity of the four wells increasing from 89.48% to 97.76%. The results show that the method, which is based on deep learning and multiparameter joint inversion, can more accurately identify porosity and has good application prospects in the prediction of carbonate reservoirs with complex structures.

Simultaneous Estimation of a Contaminant Source and Hydraulic Conductivity Field by Combining an Iterative Ensemble Smoother and Sequential Gaussian Simulation

Joint estimation of groundwater contaminant source characteristics and hydraulic conductivity is of great significance for contaminant transport models in heterogeneous subsurface media. As for accurate characterization of hydraulic conductivities, both geostatistical modeling and groundwater inverse modeling are alternative approaches. In this study, an iterative ensemble smoother and sequential gaussian simulation (SGSIM) in geostatistics modeling were combined to realize the simultaneous inversion of contaminant sources and hydraulic conductivities, by using directly measured hydraulic conductivities and indirect hydraulic head and concentration data. To alleviate the high computational cost caused by repetitive evaluations of complex, high-dimensional groundwater models, SGSIM with the pilot points method was used. Considering the characteristics of the proposed method, four scenarios with ten cases were set up in terms of ensemble number and iteration number that affect the performance of the iterative ensemble smoother, the number of pilot points, and the observation data, respectively. The results for the synthetic example indicate that the ensemble size of 2000 and the pilot point number of 80 is an ideal combination of parameters, and the proposed method can successfully recover contaminant source information simultaneously with hydraulic conductivity.

Glacier Ice Surface Properties in South‐West Greenland Ice Sheet: First Estimates From PRISMA Imaging Spectroscopy Data

AbstractSnow and ice melt processes on the Greenland Ice Sheet are a key in Earth's energy balance and are acutely sensitive to climate change. Melting dynamics are directly related to a decrease in surface albedo, amongst others caused by the accumulation of light‐absorbing particles (LAPs). Featuring unique spectral patterns, these accumulations can be mapped and quantified by imaging spectroscopy. We present first results for the retrieval of glacier ice properties from the spaceborne PRISMA imaging spectrometer by applying a recently developed simultaneous inversion of atmospheric and surface state using optimal estimation. The image analyzed in this study was acquired over the South‐West margin of the Greenland Ice Sheet in late August 2020. The area is characterized by patterns of both clean and dark ice associated with a high amount of LAPs deposited on the surface. We present retrieval maps and uncertainties for grain size, liquid water, and algae concentration, as well as estimated reflectance spectra for different surface properties. We then show the feasibility of using imaging spectroscopy to interpret multiband sensor data to achieve high accuracy, frequently repeated observations of changing snow and ice conditions. For example, the impurity index calculated from multiband Sentinel‐3 Ocean and Land Colour Instrument measurements is dependent on dust particles, but we show that algae concentration alone can be predicted from this data with less than 20% uncertainty. Our study evidences that present and upcoming orbital imaging spectroscopy missions such as PRISMA, Environmental Mapping and Analysis Program, Copernicus Hyperspectral Imaging Mission, and the Surface Biology and Geology designated observable, can significantly support research of melting ice sheets.

Simultaneous inversion of a time-dependent potential coefficient and a time source term in a time fractional diffusion-wave equation

The main purpose of this paper is to identify simultaneously a time-dependent potential coefficient and a time source term in a time fractional diffusion-wave equation from two points observed data. First of all, using the fixed point theorem, we prove the existence and uniqueness of the solution for the direct problem. Secondly, the stability of the inverse problem is proved and the uniqueness is a direct result of the stability estimate. In addition, we illustrate the ill-posedness of the inverse problem and use a non-stationary iterative Tikhonov regularization method to recover numerically the time dependent potential coefficient and source term. At the same time, we give the existence of the minimizer for the minimization functional. In order to solve the minimization problem, we apply an alternating minimization method to find the minimizer and prove the solving sub-problems are stable on noisy data as well as prove the data fidelity item decreases monotonously with the iterative running. Finally, some numerical examples are provided to shed light on the validity and robustness of the numerical algorithm.

Multi-line lasing in the broadly tunable ammonia quantum cascade laser pumped molecular laser

Gaseous ammonia has previously been demonstrated as a compelling gain medium for a quantum cascade laser pumped molecular laser (QPML) exhibiting good power efficiency. Here, we explore the potential of the ammonia QPML to produce powerful, broadly tunable terahertz frequency lasing on rotational and pure inversion transitions. After theoretically predicting possible laser frequencies, pump thresholds, and efficiencies, we experimentally demonstrate unprecedented tunability—from 0.763 to 4.459 THz—by pumping Q- and R-branch infrared transitions with widely tunable quantum cascade lasers. We additionally demonstrate two types of multi-line lasing: simultaneous pure inversion and rotation–inversion transitions from the same pumped rotational state and cascaded lasing involving transitions below the pumped rotational state. We report single frequency power levels as great as 0.45 mW from a low volume laser cavity.

RESERVOIR CHARACTERIZATION USING SIMULTANEOUS INVERSION TO DELINEATE HYDROCARBON RESERVOIR

Reservoir characterization analysis has been carried out for identifying lithology and Àuid content on TalangAkarFormation in South Sumatra Basin. Robust method that being used in this study is the simultaneous inversion which uses pre-stack gather and well log data from Puja A and Puja B. Elastic parameters resulted from simultaneous inversion are P Impedance, S Impedance and V / V ratio. Lambda-Rho parameter (lr) and Mu-Rho (mr) derived from P impedance (I ) and S impedance (I ). Lambda-Rho is sensitive to Àuid content while Mu-Rho to lithology. Area of interest in this study is Talang Akar Formation as reservoir which contains gas with Lambda-Rho (lr) between 5-15 (GPa*g/cc) and Mu-Rho (mr) 35-45 (GPa*g/cc). The ratio of P wave (Vp) and S wave (Vs) can be used as an indicator to determine Àuid saturation. Gas saturated rock has value of Vp / Vs lower than the water saturated rock. In this study, the ratio of Vp / Vs is 1.5-1.7 for gas saturated rock