Infrared spectrum image inversion method for augmenting data sets

2020 ◽  
Author(s):  
Shuai Liang ◽  
Meng Liu ◽  
Zhongyang Wang ◽  
Tianxu Zhang
Keyword(s):  
Infrared Spectrum ◽  
Inversion Method ◽  
Data Sets

scholarly journals A super-Earth and a mini-Neptune around Kepler-59

2019 ◽  
Vol 491 (4) ◽  
pp. 5238-5247 ◽  
Author(s):  
X Saad-Olivera ◽  
C F Martinez ◽  
A Costa de Souza ◽  
F Roig ◽  
D Nesvorný
Keyword(s):  
Stability Analysis ◽  
Bayesian Inference ◽  
Spectroscopic Analysis ◽  
The Other ◽  
Inversion Method ◽  
Outer Planet ◽  
Data Sets ◽  
Dynamical Study ◽  
Data Set ◽  
Orbital Parameters

ABSTRACT We characterize the radii and masses of the star and planets in the Kepler-59 system, as well as their orbital parameters. The star parameters are determined through a standard spectroscopic analysis, resulting in a mass of $1.359\pm 0.155\, \mathrm{M}_\odot$ and a radius of $1.367\pm 0.078\, \mathrm{R}_\odot$. The obtained planetary radii are $1.5\pm 0.1\, R_\oplus$ for the inner and $2.2\pm 0.1\, R_\oplus$ for the outer planet. The orbital parameters and the planetary masses are determined by the inversion of Transit Timing Variations (TTV) signals. We consider two different data sets: one provided by Holczer et al. (2016), with TTVs only for Kepler-59c, and the other provided by Rowe et al. (2015), with TTVs for both planets. The inversion method applies an algorithm of Bayesian inference (MultiNest) combined with an efficient N-body integrator (Swift). For each of the data set, we found two possible solutions, both having the same probability according to their corresponding Bayesian evidences. All four solutions appear to be indistinguishable within their 2-σ uncertainties. However, statistical analyses show that the solutions from Rowe et al. (2015) data set provide a better characterization. The first solution infers masses of $5.3_{-2.1}^{+4.0}~M_{\mathrm{\oplus }}$ and $4.6_{-2.0}^{+3.6}~M_{\mathrm{\oplus }}$ for the inner and outer planet, respectively, while the second solution gives masses of $3.0^{+0.8}_{-0.8}~M_{\mathrm{\oplus }}$ and $2.6^{+0.9}_{-0.8}~M_{\mathrm{\oplus }}$. These values point to a system with an inner super-Earth and an outer mini-Neptune. A dynamical study shows that the planets have almost co-planar orbits with small eccentricities (e < 0.1), close to the 3:2 mean motion resonance. A stability analysis indicates that this configuration is stable over million years of evolution.

An efficient data‐subspace inversion method for 2-D magnetotelluric data

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 791-803 ◽  
Author(s):  
Weerachai Siripunvaraporn ◽  
Gary Egbert
Keyword(s):  
Significant Loss ◽  
Inversion Method ◽  
Data Sets ◽  
Reduced Basis ◽  
Sensitivity Matrix ◽  
Approximate Methods ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Data Space ◽  
Occam’S Inversion

There are currently three types of algorithms in use for regularized 2-D inversion of magnetotelluric (MT) data. All seek to minimize some functional which penalizes data misfit and model structure. With the most straight‐forward approach (exemplified by OCCAM), the minimization is accomplished using some variant on a linearized Gauss‐Newton approach. A second approach is to use a descent method [e.g., nonlinear conjugate gradients (NLCG)] to avoid the expense of constructing large matrices (e.g., the sensitivity matrix). Finally, approximate methods [e.g., rapid relaxation inversion (RRI)] have been developed which use cheaply computed approximations to the sensitivity matrix to search for a minimum of the penalty functional. Approximate approaches can be very fast, but in practice often fail to converge without significant expert user intervention. On the other hand, the more straightforward methods can be prohibitively expensive to use for even moderate‐size data sets. Here, we present a new and much more efficient variant on the OCCAM scheme. By expressing the solution as a linear combination of rows of the sensitivity matrix smoothed by the model covariance (the “representers”), we transform the linearized inverse problem from the M-dimensional model space to the N-dimensional data space. This method is referred to as DASOCC, the data space OCCAM’s inversion. Since generally N ≪ M, this transformation by itself can result in significant computational saving. More importantly the data space formulation suggests a simple approximate method for constructing the inverse solution. Since MT data are smooth and “redundant,” a subset of the representers is typically sufficient to form the model without significant loss of detail. Computations required for constructing sensitivities and the size of matrices to be inverted can be significantly reduced by this approximation. We refer to this inversion as REBOCC, the reduced basis OCCAM’s inversion. Numerical experiments on synthetic and real data sets with REBOCC, DASOCC, NLCG, RRI, and OCCAM show that REBOCC is faster than both DASOCC and NLCG, which are comparable in speed. All of these methods are significantly faster than OCCAM, but are not competitive with RRI. However, even with a simple synthetic data set, we could not always get RRI to converge to a reasonable solution. The basic idea behind REBOCC should be more broadly applicable, in particular to 3-D MT inversion.

3-D resistivity inversion using the finite‐element method

Geophysics ◽  
1994 ◽  
Vol 59 (12) ◽  
pp. 1839-1848 ◽  
Author(s):  
Yutaka Sasaki
Keyword(s):  
Finite Element ◽  
Approximate Method ◽  
Synthetic Data ◽  
Computation Time ◽  
Inversion Method ◽  
Data Sets ◽  
Near Surface ◽  
Partial Derivatives ◽  
Homogeneous Half Space ◽  
Resistivity Inversion

With the increased availability of faster computers, it is now practical to employ numerical modeling techniques to invert resistivity data for 3-D structure. Full and approximate 3-D inversion methods using the finite‐element solution for the forward problem have been developed. Both methods use reciprocity for efficient evaluations of the partial derivatives of apparent resistivity with respect to model resistivities. In the approximate method, the partial derivatives are approximated by those for a homogeneous half‐space, and thus the computation time and memory requirement are further reduced. The methods are applied to synthetic data sets from 3-D models to illustrate their effectiveness. They give a good approximation of the actual 3-D structure after several iterations in practical situations where the effects of model inadequacy and topography exist. Comparisons of numerical examples show that the full inversion method gives a better resolution, particularly for the near‐surface features, than does the approximate method. Since the full derivatives are more sensitive to local features of resistivity variations than are the approximate derivatives, the resolution of the full method may be further improved when the finite‐element solutions are performed more accurately and more efficiently.

scholarly journals Revising the retrieval technique of a long-term stratospheric HNO<sub>3</sub> data set: from a constrained matrix inversion to the optimal estimation algorithm

2011 ◽  
Vol 29 (7) ◽  
pp. 1317-1330 ◽  
Author(s):  
I. Fiorucci ◽  
G. Muscari ◽  
R. L. de Zafra
Keyword(s):  
Optimal Estimation ◽  
Matrix Inversion ◽  
The Arctic ◽  
Inversion Method ◽  
Data Sets ◽  
Vertical Profiles ◽  
Mixing Ratio ◽  
Data Set ◽  
The Antarctic

Abstract. The Ground-Based Millimeter-wave Spectrometer (GBMS) was designed and built at the State University of New York at Stony Brook in the early 1990s and since then has carried out many measurement campaigns of stratospheric O3, HNO3, CO and N2O at polar and mid-latitudes. Its HNO3 data set shed light on HNO3 annual cycles over the Antarctic continent and contributed to the validation of both generations of the satellite-based JPL Microwave Limb Sounder (MLS). Following the increasing need for long-term data sets of stratospheric constituents, we resolved to establish a long-term GMBS observation site at the Arctic station of Thule (76.5° N, 68.8° W), Greenland, beginning in January 2009, in order to track the long- and short-term interactions between the changing climate and the seasonal processes tied to the ozone depletion phenomenon. Furthermore, we updated the retrieval algorithm adapting the Optimal Estimation (OE) method to GBMS spectral data in order to conform to the standard of the Network for the Detection of Atmospheric Composition Change (NDACC) microwave group, and to provide our retrievals with a set of averaging kernels that allow more straightforward comparisons with other data sets. The new OE algorithm was applied to GBMS HNO3 data sets from 1993 South Pole observations to date, in order to produce HNO3 version 2 (v2) profiles. A sample of results obtained at Antarctic latitudes in fall and winter and at mid-latitudes is shown here. In most conditions, v2 inversions show a sensitivity (i.e., sum of column elements of the averaging kernel matrix) of 100 ± 20 % from 20 to 45 km altitude, with somewhat worse (better) sensitivity in the Antarctic winter lower (upper) stratosphere. The 1σ uncertainty on HNO3 v2 mixing ratio vertical profiles depends on altitude and is estimated at ~15 % or 0.3 ppbv, whichever is larger. Comparisons of v2 with former (v1) GBMS HNO3 vertical profiles, obtained employing the constrained matrix inversion method, show that v1 and v2 profiles are overall consistent. The main difference is at the HNO3 mixing ratio maximum in the 20–25 km altitude range, which is smaller in v2 than v1 profiles by up to 2 ppbv at mid-latitudes and during the Antarctic fall. This difference suggests a better agreement of GBMS HNO3 v2 profiles with both UARS/ and EOS Aura/MLS HNO3 data than previous v1 profiles.

Time-lapse acoustic impedance variations during CO2 injection in Weyburn oilfield, Canada

Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. M1-M13 ◽  
Author(s):  
Yichuan Wang ◽  
Igor B. Morozov
Keyword(s):  
Oil Recovery ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Time Lapse ◽  
Time Shift ◽  
Co2 Injection ◽  
Inversion Method ◽  
Data Sets ◽  
Storage Site ◽  
Data Set

For seismic monitoring injected fluids during enhanced oil recovery or geologic [Formula: see text] sequestration, it is useful to measure time-lapse (TL) variations of acoustic impedance (AI). AI gives direct connections to the mechanical and fluid-related properties of the reservoir or [Formula: see text] storage site; however, evaluation of its subtle TL variations is complicated by the low-frequency and scaling uncertainties of this attribute. We have developed three enhancements of TL AI analysis to resolve these issues. First, following waveform calibration (cross-equalization) of the monitor seismic data sets to the baseline one, the reflectivity difference was evaluated from the attributes measured during the calibration. Second, a robust approach to AI inversion was applied to the baseline data set, based on calibration of the records by using the well-log data and spatially variant stacking and interval velocities derived during seismic data processing. This inversion method is straightforward and does not require subjective selections of parameterization and regularization schemes. Unlike joint or statistical inverse approaches, this method does not require prior models and produces accurate fitting of the observed reflectivity. Third, the TL AI difference is obtained directly from the baseline AI and reflectivity difference but without the uncertainty-prone subtraction of AI volumes from different seismic vintages. The above approaches are applied to TL data sets from the Weyburn [Formula: see text] sequestration project in southern Saskatchewan, Canada. High-quality baseline and TL AI-difference volumes are obtained. TL variations within the reservoir zone are observed in the calibration time-shift, reflectivity-difference, and AI-difference images, which are interpreted as being related to the [Formula: see text] injection.

Simultaneous Joint Migration Inversion with calendar-time constraints as a processing tool for semi-continuous surveys

Geophysics ◽  
2021 ◽  
pp. 1-90
Author(s):  
Shan Qu ◽  
Eric Verschuur
Keyword(s):  
Low Cost ◽  
Time Lapse ◽  
Time Constraints ◽  
Inversion Method ◽  
Data Sets ◽  
Time Axis ◽  
Calendar Time ◽  
Full Field ◽  
Simultaneous Inversion ◽  
Frequent Monitoring

Nowadays, to obtain a better understanding of dynamic time-lapse changes, frequent seismic monitoring is necessary, although it will generate a considerable cost increase. Therefore, low-cost frequent monitoring, e.g., sparse and/or nonrepeated surveys, is desired. The simultaneous inversion-based method allows the baseline and monitor parameters to communicate and compensate with each other during inversion via constraints and helps to reduce the artifacts caused by sparse acquisition. These features make it largely independent of the used low-cost acquisition geometry and suitable for inexpensive frequent monitoring surveys. Therefore, we have used this simultaneous inversion-based method as an effective time-lapse processing tool for data sets acquired from inexpensive, semicontinuous time-lapse monitoring surveys, which are based on the so-called instantaneous 4D (i4D) technology. We choose a specific simultaneous inversion method called simultaneous joint migration inversion (S-JMI), which combines a simultaneous processing strategy with the JMI method. In i4D technology, inexpensive localized/sparse surveys, called i4D surveys, are deployed frequently between the conventional full-field surveys. This technology can be treated as a special case of changing geometries during monitoring. In this case, the simultaneous strategy allows the information of the full-field survey to compensate for the insufficient illumination of the localized/sparse i4D surveys during processing. Furthermore, we apply constraints on the reflectivity and velocity differences between the baseline and monitor vintages along the calendar-time axis called calendar-time constraints. These constraints take advantage of the feature that time-lapse effects develop (semi)continuously along the calendar-time axis, when the monitoring surveys are deployed (semi)continuously over calendar time. Based on a complex synthetic example, we determined that S-JMI is a promising tool to process the data sets from the semicontinuous monitoring surveys based on i4D technology. Finally, we found that the calendar-time constraints significantly improve the quality of time-lapse effects.

SH-SH wave inversion for S-wave velocity and density

Geophysics ◽  
2022 ◽  
pp. 1-59
Author(s):  
Fucai Dai ◽  
Feng Zhang ◽  
Xiangyang Li
Keyword(s):  
Wave Velocity ◽  
Inversion Method ◽  
Data Sets ◽  
Sh Wave ◽  
S Wave ◽  
Data Set ◽  
Sh Waves ◽  
Model Parameter ◽  
Wave Inversion ◽  
Impedance Contrast

SS-waves (SV-SV waves and SH-SH waves) are capable of inverting S-wave velocity ( VS) and density ( ρ) because they are sensitive to both parameters. SH-SH waves can be separated from multicomponent data sets more effectively than the SV-SV wave because the former is decoupled from the PP-wave in isotropic media. In addition, the SH-SH wave can be better modeled than the SV-SV wave in the case of strong velocity/impedance contrast because the SV-SV wave has multicritical angles, some of which can be quite small when velocity/ impedance contrast is strong. We derived an approximate equation of the SH-SH wave reflection coefficient as a function of VS and ρ in natural logarithm variables. The approximation has high accuracy, and it enables the inversion of VS and ρ in a direct manner. Both coefficients corresponding to VS and ρ are “model-parameter independent” and thus there is no need for prior estimate of any model parameter in inversion. Then, we developed an SH-SH wave inversion method, and demonstrated it by using synthetic data sets and a real SH-SH wave prestack data set from the west of China. We found that VS and ρ can be reliably estimated from the SH-SH wave of small angles.

Closing the global and regional sea level budgets by combining multi-mission altimetry and GRACE(-FO) data

2020 ◽  
Author(s):  
Bernd Uebbing ◽  
Christina Lück ◽  
Roelof Rietbroek ◽  
Kristin Vielberg ◽  
Jürgen Kusche
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Sea Level Change ◽  
Inversion Method ◽  
Data Sets ◽  
Sea Level Changes ◽  
Steric Sea Level ◽  
Level Change ◽  
Spatial Coverage ◽  
Regional Sea Level

&lt;p&gt;Understanding present day sea level changes and their drivers requires the separation of the total sea level change into individual mass and steric related contributions. Total sea level rise has been observed continuously since 1993 providing a more than 25 year long time series of global and regional sea level variations. However, direct monitoring of ocean mass change has only been done since the start of the Gravity Recovery And Climate Experiment (GRACE) mission in 2002. It ended in 2017 and was succeeded by the follow-on mission (GRACE-FO) in 2018 leaving a gap of about 1 year. In the same time period of GRACE, since the early 2000s, a global array of freely drifting Argo floats samples temperature and salinity profiles of up to 2000m depth which can be converted to steric sea level change.&lt;/p&gt;&lt;p&gt;By combining altimetry, GRACE(-FO) and Argo data sets it is possible to derive global and regional sea level budgets. The conventional approach is to analyze at least two of the data sets and derive the residual, or compare with the third one. A more recent approach is the global joint inversion method (Rietbroek et al., 2016) which fits forward-modeled spatial fingerprints to a combination of GRACE gravity data and Jason-1/-2 satellite altimetry data. This enables us, additionally, to separate altimetric sea level change into mass contributions from terrestrial hydrology, the melting of land glaciers and the ice-sheets in Greenland and Antarctica as well as contributions from steric sea level changes due to variations in ocean temperature and salinity. It also allows to include a data weighting scheme in the analysis.&lt;/p&gt;&lt;p&gt;Here, we present global and regional sea level budget results from an updated inversion based on multi-mission altimetry (Jason-1/-2/-3, Envisat, Cryosat-2, Sentinel-3, &amp;#8230;) providing better spatial coverage as well as new RL06 GRACE and GRACE-FO data which enables us to extend the time series of individual components of the sea level budget beyond the GRACE era from 2002-04 till 2019-06. The presented sea level budget is closed on global scale with a residual (unexplained) contribution of about 0.1 mm/yr, globally, originating in eddy-active regions. We provide consistent validation of our results against conventionally analyzed altimetry and GRACE data sets where we find agreement on global scales to be better than 0.1 mm/yr but a larger disagreement at regional scales as well as the implications of our results for deriving ocean heat content. We will also provide first results for filling the gap in the sea level budget estimates due to the gap between the GRACE and GRACE-FO missions by additionally incorporating time-variable gravity information from the Swarm mission as well as from Satellite Laser Ranging (SLR) to 5 satellites (Lageos-1/-2, Stella, Starlette, Ajisai).&lt;/p&gt;

A rapid four-dimensional resistivity data inversion method using temporal segmentation

2020 ◽  
Vol 221 (1) ◽  
pp. 586-602 ◽  
Author(s):  
Bin Liu ◽  
Yonghao Pang ◽  
Deqiang Mao ◽  
Jing Wang ◽  
Zhengyu Liu ◽  
...  
Keyword(s):  
Current Data ◽  
Inversion Method ◽  
Data Sets ◽  
Temporal Segmentation ◽  
Data Set ◽  
Subsurface Structures ◽  
Data Inversion ◽  
Rapid Changes ◽  
High Level ◽  
Acquisition Cycle

SUMMARY 4-D electrical resistivity tomography (ERT), an important geophysical method, is widely used to observe dynamic processes within static subsurface structures. However, because data acquisition and inversion consume large amounts of time, rapid changes that occur in the medium during a single acquisition cycle are difficult to detect in a timely manner via 4-D inversion. To address this issue, a scheme is proposed in this paper for restructuring continuously measured data sets and performing GPU-parallelized inversion. In this scheme, multiple reference time points are selected in an acquisition cycle, which allows all of the acquired data to be sequentially utilized in a 4-D inversion. In addition, the response of the 4-D inversion to changes in the medium has been enhanced by increasing the weight of new data being added dynamically to the inversion process. To improve the reliability of the inversion, our scheme uses actively varied time-regularization coefficients, which are adjusted according to the range of the changes in model resistivity; this range is predicted by taking the ratio between the independent inversion of the current data set and historical 4-D inversion model. Numerical simulations and experiments show that this new 4-D inversion method is able to locate and depict rapid changes in medium resistivity with a high level of accuracy.

Six Major Historical Earthquakes in the Seoul Metropolitan Area during the Joseon Dynasty (1392–1910)

2020 ◽  
Vol 110 (6) ◽  
pp. 3037-3049 ◽  
Author(s):  
Seongjun Park ◽  
Inho Baek ◽  
Tae-Kyung Hong
Keyword(s):  
South Korea ◽  
Seismic Hazard ◽  
Metropolitan Area ◽  
Joint Inversion ◽  
Historical Earthquakes ◽  
Seismic Damage ◽  
Inversion Method ◽  
Data Sets ◽  
Seoul Metropolitan Area ◽  
Joseon Dynasty

ABSTRACT Earthquake records in the historical literature provide valuable information on the seismic hazard potentials for long recurrence times. The Seoul metropolitan area is the center of the economy and infrastructure in South Korea. Six major earthquakes that occurred around the Seoul metropolitan area during the Joseon dynasty in 1392–1910 are analyzed using a probabilistic joint inversion method based on seismic damage records and earthquake-felt reports. The inversion yields sets of event locations and magnitudes with probabilities. The joint inversion method is validated with synthetic and instrumentally observed data sets. The historical earthquakes are found to be located around the Seoul metropolitan area. The magnitudes of the earthquakes range from ML 5.3 to 6.8 at the peak probabilistic locations. These historical earthquakes suggest considerable seismic hazard potentials in the Seoul metropolitan area.

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