On the accuracy and efficiency of the joint source scanning algorithm for hydraulic fracturing monitoring

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. KS77-KS85 ◽  
Author(s):  
Yangyang Yu ◽  
Chuntao Liang ◽  
Furong Wu ◽  
Xuben Wang ◽  
Gang Yu ◽  
...  
Keyword(s):  
Field Data ◽  
Joint Inversion ◽  
Synthetic Data ◽  
Computation Time ◽  
Focal Mechanisms ◽  
Inversion Method ◽  
Actual Field ◽  
Microseismic Events ◽  
Reduce Computation Time ◽  
Scanning Algorithm

We have developed the joint source scanning algorithm (JSSA) to determine the locations and focal mechanisms (FMs) of microseismic events simultaneously. However, the computational expense of using JSSA is too high to meet the requirements of real-time monitoring in industrial production. We have developed several scanning schemas to reduce computation time. A multistage scanning schema can significantly improve efficiency while retaining accuracy. For the optimized joint inversion method, a series of tests has been carried out using actual field data and synthetic data to evaluate the accuracy of the method, as well as its dependence on the noise level, source depths, FMs, and other factors. The surface-based arrays better constrain horizontal location errors ([Formula: see text]) and angular errors of P-axes (within 10° for [Formula: see text]). For sources with varying rakes, dips, strikes, and depths, the errors are mostly controlled by the partition of positive and negative polarities in different quadrants. More evenly partitioned polarities in different quadrants yield better results for locations and FMs. Nevertheless, even when some FMs have bad resolutions, the optimized JSSA method can still significantly improve location accuracies.

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 Adaptive moment-tensor joint inversion of clustered microseismic events for monitoring geological carbon storage

2019 ◽  
Vol 219 (1) ◽  
pp. 80-93
Author(s):  
Yu Chen ◽  
Lianjie Huang
Keyword(s):  
Carbon Storage ◽  
Oil Recovery ◽  
Joint Inversion ◽  
Moment Tensor ◽  
Crack Opening ◽  
Cost Effective ◽  
Microseismic Monitoring ◽  
Moment Tensor Inversion ◽  
Inversion Method ◽  
Microseismic Events

SUMMARY Moment-tensor inversion of induced microseismic events can provide valuable information for tracking CO2 plumes at geological carbon storage sites, and study the physical mechanism of induced microseismicity. Accurate moment-tensor inversion requires a wide-azimuthal coverage of geophones. Cost-effective microseismic monitoring for geological carbon storage often uses only one geophone array within a borehole, leading to a large uncertainty in moment-tensor inversion. We develop a new adaptive moment-tensor joint inversion method to reduce the inversion uncertainty, when using limited but typical geophone receiver geometries. We first jointly invert a number of clustered microseismic events using a uniform focal mechanism to minimize the waveform misfit between observed and predicted P and S waveforms. We then invert the moment tensor for each event within a limited searching range around the joint inversion result. We apply our adaptive joint inversion method to microseismic data acquired using a single borehole geophone array at the CO2-Enhanced Oil Recovery field at Aneth, Utah. We demonstrate that our inversion method is capable of reducing the inversion uncertainty caused by the limited azimuthal coverage of geophones. Our inverted strikes of focal mechanisms of microseismic events are consistent with the event spatial distribution in subparallel pre-existing fractures or geological imperfections. The large values up to 40 per cent of the CLVD components might indicate crack opening induced by CO2/wastewater injection or rupture complexity.

Microseismic denoising assessment by polarization histograms

Geophysics ◽  
2020 ◽  
pp. 1-46
Author(s):  
German I. Brunini ◽  
Juan I. Sabbione ◽  
Julián L. Gómez ◽  
Danilo R. Velis
Keyword(s):  
Singular Value Decomposition ◽  
Quality Factor ◽  
Field Data ◽  
Synthetic Data ◽  
Singular Value ◽  
Mode Decomposition ◽  
Actual Field ◽  
Band Pass ◽  
Value Decomposition ◽  
Better Than

We present a comparison of microseismic data denoising methods based on their effect on the polarization attributes of 3C microseismic signals. The compared denoising methods include the classical band-pass filtering, and three recently proposed denoising techniques: restricted domain hyperbolic Radon transform denoising, singular value decomposition-based reduced-rank filtering, and empirical mode decomposition denoising. In order to draw the comparison, we have denoised 3C synthetic data contaminated with noise extracted from actual field data records, calculated their rectilinearity, azimuth, and dip polarization attributes, and arranged them into histograms. The comparison has been drawn by measuring the distances between the polarization histograms of the clean and denoised data, assuming that one method outperforms another if the aforementioned distance is smaller. This strategy allows to quantify the improvement in the calculated polarization attributes due to the different denoising processes. In addition, we have also calculated the quality factor of the denoised signals, which adds value and robustness to the comparison. Our results have indicated that the method based on singular value decomposition preserves the original polarization attributes better than the other techniques tested in this work. Moreover, it has also retrieved the denoised signal with the highest quality factor. Finally, we have tested the methods with field data and assessed their performance qualitatively on the basis of the insight gained from the numerical tests with synthetic data.

A ray inversion method for refraction analysis

Geophysics ◽  
1985 ◽  
Vol 50 (11) ◽  
pp. 1701-1720 ◽  
Author(s):  
Glyn M. Jones ◽  
D. B. Jovanovich
Keyword(s):  
Field Data ◽  
Opposite Sign ◽  
Synthetic Data ◽  
Head Wave ◽  
Inversion Method ◽  
Data Set ◽  
Near Surface ◽  
Left And Right ◽  
A New Technique ◽  
Good Agreement

A new technique is presented for the inversion of head‐wave traveltimes to infer near‐surface structure. Traveltimes computed along intersecting pairs of refracted rays are used to reconstruct the shape of the first refracting horizon beneath the surface and variations in refractor velocity along this boundary. The information derived can be used as the basis for further processing, such as the calculation of near‐surface static delays. One advantage of the method is that the shape of the refractor is determined independently of the refractor velocity. With multifold coverage, rapid lateral changes in refractor geometry or velocity can be mapped. Two examples of the inversion technique are presented: one uses a synthetic data set; the other is drawn from field data shot over a deep graben filled with sediment. The results obtained using the synthetic data validate the method and support the conclusions of an error analysis, in which errors in the refractor velocity determined using receivers to the left and right of the shots are of opposite sign. The true refractor velocity therefore falls between the two sets of estimates. The refraction image obtained by inversion of the set of field data is in good agreement with a constant‐velocity reflection stack and illustrates that the ray inversion method can handle large lateral changes in refractor velocity or relief.

scholarly journals OpenMP Implementation of a Novel Potential-Field-Data Source-Growth-Based Inversion Approach for 3D Salt Imaging in Deepwater Gulf of Mexico

2020 ◽  
Vol 10 (14) ◽  
pp. 4798
Author(s):  
Naín Vera ◽  
Carlos Couder-Castañeda ◽  
Jorge Hernández ◽  
Alfredo Trujillo-Alcántara ◽  
Mauricio Orozco-del-Castillo ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Potential Field ◽  
Field Data ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Complex Salt ◽  
Research Field ◽  
Inversion Method ◽  
Potential Field Data ◽  
Simultaneous Inversion

Potential-field-data imaging of complex geological features in deepwater salt-tectonic regions in the Gulf of Mexico remains an open active research field. There is still a lack of resolution in seismic imaging methods below and in the surroundings of allochthonous salt bodies. In this work, we present a novel three-dimensional potential-field-data simultaneous inversion method for imaging of salt features. This new approach incorporates a growth algorithm for source estimation, which progressively recovers geological structures by exploring a constrained parameter space; restrictions are posed from a priori geological knowledge of the study area. The algorithm is tested with synthetic data corresponding to a real complex salt-tectonic geological setting commonly found in exploration areas of deepwater Gulf of Mexico. Due to the huge amount of data involved in three-dimensional inversion of potential field data, the use of parallel computing techniques becomes mandatory. In this sense, to alleviate computational burden, an easy to implement parallelization strategy for the inversion scheme through OpenMP directives is presented. The methodology was applied to invert and integrate gravity, magnetic and full tensor gradient data of the study area.

A Bayesian model for gas saturation estimation using marine seismic AVA and CSEM data

Geophysics ◽  
2007 ◽  
Vol 72 (2) ◽  
pp. WA85-WA95 ◽  
Author(s):  
Jinsong Chen ◽  
G. Michael Hoversten ◽  
Donald Vasco ◽  
Yoram Rubin ◽  
Zhangshuan Hou
Keyword(s):  
Bayesian Model ◽  
Field Data ◽  
Time Window ◽  
Joint Inversion ◽  
Synthetic Data ◽  
Shear Moduli ◽  
Unknown Variable ◽  
Gas Saturation ◽  
Fluid Saturation ◽  
Marine Seismic

We develop a Bayesian model to jointly invert marine seismic amplitude versus angle (AVA) and controlled-source electromagnetic (CSEM) data for a layered reservoir model. We consider the porosity and fluid saturation of each layer in the reservoir, the bulk and shear moduli and density of each layer not in the reservoir, and the electrical conductivity of the overburden and bedrock as random variables. We also consider prestack seismic AVA data in a selected time window as well as real and quadrature components of the recorded electrical field as data. Using Markov chain Monte Carlo (MCMC) sampling methods, wedraw a large number of samples from the joint posterior distribution function. With these samples, we obtain not only the estimates of each unknown variable, but also various types of uncertainty information associated with the estimation. This method is applied to both synthetic and field data to investigate the combined use of seismic AVA and CSEM data for gas saturation estimation. Results show that the method is effective for joint inversion; the incorporation of CSEM data reduces uncertainty in fluid saturation estimation compared to inversion of seismic AVA data alone. The improvement in gas saturation estimation obtained from joint inversion for field data is less significant than for synthetic data because of the large number of unknown noise sources inherent in the field data.

Joint inversion of logging-while-drilling multipole acoustic data to determine formation shear-wave transverse isotropy

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. D121-D132
Author(s):  
Yang-Hu Li ◽  
Song Xu ◽  
Can Jiang ◽  
Yuan-Da Su ◽  
Xiao-Ming Tang
Keyword(s):  
Shear Wave ◽  
Joint Inversion ◽  
Transverse Isotropy ◽  
Synthetic Data ◽  
Flexural Wave ◽  
Inversion Method ◽  
S Wave ◽  
Acoustic Data ◽  
Wave Data ◽  
Logging While Drilling

Seismic-wave anisotropy has long been an important topic in the exploration and development of unconventional reservoirs, especially in shales, which are commonly characterized as transversely isotropic ([TI] or vertical TI [VTI]) media. At present, the shear-wave (S-wave) TI properties have mainly been determined from monopole Stoneley- or dipole flexural-wave measurements in wireline acoustic logging, but the feasibility of those obtained from logging-while-drilling (LWD) acoustic data needs to be established. We have developed a joint inversion method for simultaneously determining formation S-wave transverse isotropy and vertical velocity from LWD multipole acoustic data. Our theoretical analysis shows that the presence of anisotropy strongly influences LWD Stoneley- and quadrupole-wave dispersion characteristics. Although the monopole Stoneley and quadrupole waves are sensitive to the formation S-wave TI parameters, they suffer from the typical nonuniqueness problem when using the individual-wave data to invert parameters alone. Thus, the respective dispersion data can be jointly used to estimate the formation S-wave TI properties. By the joint inversion, the nonuniqueness problem in the parameter inversion can also be effectively alleviated. The feasibility of the method has been verified by the processing results of theoretical synthetic data and field LWD acoustic-wave data. Therefore, the result offers an effective method for evaluating VTI formation anisotropy from acoustic LWD data.

An Improved 3D Joint Inversion Method of Potential Field Data Using Cross-Gradient Constraint and LSQR Method

2018 ◽  
Vol 175 (12) ◽  
pp. 4389-4409 ◽  
Author(s):  
Farshad Joulidehsar ◽  
Ali Moradzadeh ◽  
Faramarz Doulati Ardejani
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Joint Inversion ◽  
Inversion Method ◽  
Potential Field Data ◽  
Gradient Constraint

Two‐dimensional joint inversion of magnetotelluric and dipole‐dipole resistivity data

Geophysics ◽  
1989 ◽  
Vol 54 (2) ◽  
pp. 254-262 ◽  
Author(s):  
Yutaka Sasaki
Keyword(s):  
Field Data ◽  
Least Squares Method ◽  
Joint Inversion ◽  
Computation Time ◽  
Schmidt Method ◽  
The Finite Element Method ◽  
Data Set ◽  
Resistivity Data ◽  
D Model ◽  
Derivatives Of

This paper describes 2-D joint inversion of MT and dipole‐dipole resistivity data with the emphasis on the computer algorithm. The algorithm produces a 2-D model composed of a large number of rectangular blocks, each of which has constant resistivity. The solutions to two forward problems are based on the finite‐element method. The computation time for the partial derivatives of MT responses is reduced by using the reciprocity relation and the concept of a fictitious source. The smoothness‐constrained least‐squares method, together with the modified Gram‐Schmidt method, is also to stabilize the solution and avoid spurious resistivity features. Synthetic and field data examples show that the 2-D joint inversion can be effective for improving the resolution attained by the 2-D interpretation of a single kind of data set.

Sign in / Sign up

Export Citation Format

Share Document