Deep learning-based artificial bandwidth extension: Training on ultrasparse OBN to enhance towed-streamer FWI

2020 ◽  
Vol 39 (10) ◽  
pp. 718-726
Author(s):  
Mehdi Aharchaou ◽  
Anatoly Baumstein
Keyword(s):  
Model Building ◽  
Opportunity To Learn ◽  
Supervised Machine Learning ◽  
Seismic Exploration ◽  
Large Field ◽  
High Signal ◽  
Ocean Bottom ◽  
Bandwidth Extension ◽  
Low Frequencies ◽  
Streamer Data

The lack of seismic low frequencies in towed-streamer data is known to have an outsized detrimental effect on advanced velocity model building techniques such as full-waveform inversion (FWI). Since seabed acquisition records ultralow frequencies (1–4 Hz) with high signal-to-noise ratio, this presents an opportunity to learn, in a supervised machine learning fashion, a bandwidth extension function to enrich towed-streamer data with low frequencies. We use recent advances in training deep neural networks to develop a novel method for learning low-frequency reconstruction from an ultrasparse set of ocean-bottom nodes (OBNs). This bandwidth extension is tested on two large field data sets (from an OBN survey and a wide-azimuth towed-steamer survey) acquired over a complex-shaped salt region in the Gulf of Mexico. The reconstructed low frequencies, although not perfect, enable FWI to more effectively correct the shape of salt bodies and result in improved subsalt imaging. Well-tie analysis shows an improvement in phase stability around the wellbore and a fit to within half a cycle at reservoir level. This work links together towed-streamer and seabed acquisitions, providing a cost-effective solution to help offshore seismic exploration with higher-quality low frequencies.

scholarly journals Low-Frequency Expansion Approach for Seismic Data Based on Compressed Sensing in Low SNR

2021 ◽  
Vol 11 (11) ◽  
pp. 5028
Author(s):  
Miaomiao Sun ◽  
Zhenchun Li ◽  
Yanli Liu ◽  
Jiao Wang ◽  
Yufei Su
Keyword(s):  
Reflection Coefficient ◽  
Compressed Sensing ◽  
Objective Function ◽  
Low Frequency ◽  
Original Data ◽  
Seismic Exploration ◽  
High Signal ◽  
Inversion Process ◽  
Frequency Information ◽  
Low Snr

Low-frequency information can reflect the basic trend of a formation, enhance the accuracy of velocity analysis and improve the imaging accuracy of deep structures in seismic exploration. However, the low-frequency information obtained by the conventional seismic acquisition method is seriously polluted by noise, which will be further lost in processing. Compressed sensing (CS) theory is used to exploit the sparsity of the reflection coefficient in the frequency domain to expand the low-frequency components reasonably, thus improving the data quality. However, the conventional CS method is greatly affected by noise, and the effective expansion of low-frequency information can only be realized in the case of a high signal-to-noise ratio (SNR). In this paper, well information is introduced into the objective function to constrain the inversion process of the estimated reflection coefficient, and then, the low-frequency component of the original data is expanded by extracting the low-frequency information of the reflection coefficient. It has been proved by model tests and actual data processing results that the objective function of estimating the reflection coefficient constrained by well logging data based on CS theory can improve the anti-noise interference ability of the inversion process and expand the low-frequency information well in the case of a low SNR.

Characteristics of Low-Frequency Horizontal Noise of Ocean-Bottom Seismic Data

2021 ◽  
Author(s):  
Chao An ◽  
Chen Cai ◽  
Lei Zhou ◽  
Ting Yang
Keyword(s):  
Water Waves ◽  
Noise Source ◽  
Random Noise ◽  
Low Frequency ◽  
Ocean Bottom ◽  
Coherent Noise ◽  
Infragravity Waves ◽  
Low Frequencies ◽  
Bottom Currents ◽  
Ocean Bottom Seismographs

Abstract Horizontal records of ocean-bottom seismographs are usually noisy at low frequencies (< 0.1 Hz). The noise source is believed to be associated with ocean-bottom currents that may tilt the instrument. Currently horizontal records are mainly used to remove the coherent noise in vertical records, and there has been little literature that quantitatively discusses the mechanism and characteristics of low-frequency horizontal noise. In this article, we analyze in situ ocean-bottom measurements by rotating the data horizontally and evaluating the coherency between different channels. Results suggest that the horizontal noise consists of two components, random noise and principle noise whose direction barely changes in time. The amplitude and the direction of the latter are possibly related to the intensity and direction of ocean-bottom currents. Rotating the horizontal records to the direction of the principle noise can largely suppress the principle noise in the orthogonal horizontal channel. In addition, the horizontal noise is incoherent with pressure, indicating that the noise source is not ocean surface water waves (infragravity waves). At some stations in shallow waters (<300 m), horizontal noise around 0.07 Hz is found to be linearly proportional to the temporal derivative of pressure, which is explained by forces of added mass due to infragravity waves.

A variety of surface waves in ocean-bottom DAS records

2021 ◽  
Author(s):  
Zack Spica ◽  
Loïc Viens ◽  
Jorge Castillo Castellanos ◽  
Takeshi Akuhara ◽  
Kiwamu Nishida ◽  
...  
Keyword(s):  
Surface Wave ◽  
Acoustic Waves ◽  
Fiber Optic ◽  
Acoustic Noise ◽  
Seismic Exploration ◽  
Ocean Bottom ◽  
Wide Range ◽  
Ocean Layer ◽  
Noise Cross Correlation ◽  
Low Amplitude

<p>Distributed acoustic sensing (DAS) can transform existing telecommunication fiber-optic cables into arrays of thousands of sensors, enabling meter-scale recordings over tens of kilometers. Recently, DAS has demonstrated its utility for many seismological applications onshore. However, the use of offshore cables for seismic exploration and monitoring is still in its infancy.<br>In this work, we introduce some new results and observations obtained from a fiber-optic cable offshore the coast of Sanriku, Japan. In particular, we focus on surface wave retrieved from various signals and show that ocean-bottom DAS can be used to extract dispersion curves (DC) over a wide range of frequencies. We show that multi-mode DC can be easily extracted from ambient seismo-acoustic noise cross-correlation functions or F-K analysis. Moderate magnitude earthquakes also contain multiple surface-wave packets that are buried within their coda. Fully-coupled 3-D numerical simulations suggest that these low-amplitude signals originate from the continuous reverberations of the acoustic waves in the ocean layer. </p>

scholarly journals Frequency Response Stabilization and Comparative Studies of MET Hydrophone at Marine Seismic Exploration Systems

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1944 ◽  
Author(s):  
Egor Egorov ◽  
Anna Shabalina ◽  
Dmitry Zaitsev ◽  
Sergey Kurkov ◽  
Nikolay Gueorguiev
Keyword(s):  
Frequency Response ◽  
Field Tests ◽  
High Sensitivity ◽  
Seismic Exploration ◽  
Joint Stock Company ◽  
Experimental Sample ◽  
Frequency Range ◽  
Stock Company ◽  
Low Frequencies ◽  
Marine Seismic

Low frequency hydrophone with a frequency range of 1−300 Hz for marine seismic exploration systems has been developed. The operation principle of the hydrophone bases on the molecular electronic transfer that allows high sensitivity and low level self-noise at low frequencies (<10 Hz) to be achieved. The paper presents a stabilization method of the frequency response within the frequency range at a depth up to 30 m. Laboratory and marine tests confirmed the stated characteristics as well as the possibility of using this sensor in bottom marine seismic systems. An experimental sample of the hydrophone successfully passed a comparative marine test at Gelendzhik Bay (Black Sea) with the technical support of Joint-Stock Company (JSC) “Yuzhmorgeologiya”. One of the main results is the possibility of obtaining high-quality information in the field of low frequencies, which was demonstrated in the course of field tests.

L1 pseudo-Vz estimation and deghosting of single-component marine towed-streamer data

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. WA21-WA6 ◽  
Author(s):  
Ralf Ferber ◽  
Philippe Caprioli ◽  
Lee West
Keyword(s):  
Particle Motion ◽  
Pressure Wave ◽  
Vertical Component ◽  
Low Frequency ◽  
Single Component ◽  
Pressure Data ◽  
Data Set ◽  
Low Frequencies ◽  
Motion Data ◽  
Streamer Data

We present a novel technique estimating the vertical component of particle motion from marine single-component pressure data. The particle motion data, bar an angle-dependent obliquity factor, is computed by convolution of the output from L1 deconvolution of the pressure ghost wavelet with the corresponding ghost wavelet of the particle motion. The estimated particle motion data is then used in a conventional 2D technique for receiver ghost attenuation by combination with the original pressure-wave data. The proposed new technique operates in the τ-[Formula: see text] domain of individual shot-streamer records and in overlapping windows along the intercept-time axis. In each window, the L1 deconvolution is achieved by an iteratively reweighted-norm least squares algorithm. We applied our technique to deep-tow streamer data of a 3D over/sparse-under marine survey, in which six streamers were towed at a shallow depth, with two additional streamers towed deeper. Over/sparse-under technology allows using seismic measurements from a shallow streamer to be complemented by a low-frequency limited measurement from a deep streamer to achieve an estimate of the up-going pressure wave recording. The low frequencies of the deep streamer are used to boost the low frequencies of the shallow streamer, which have been heavily attenuated by the shallow tow ghost response. Our technique achieves, on this particular data, set improvements in bandwidth of the single-component pressure data, while not fully reaching the quality of the optimally deghosted data from the over/sparse-under survey.

Velocity model building for variable-depth streamer data: Brunei case study

2013 ◽  
Author(s):  
Fatiha Gamar-Sadat ◽  
Olivier Michot ◽  
Robert Soubaras ◽  
Geoffroy Pignot ◽  
Amir Kabbej
Keyword(s):  
Model Building ◽  
Velocity Model ◽  
Variable Depth ◽  
Velocity Model Building ◽  
Streamer Data

scholarly journals Development of high-precision distributed wireless microseismic acquisition stations

2018 ◽  
Author(s):  
Shuaiqing Qiao ◽  
Hongmei Duan ◽  
Qisheng Zhang ◽  
Qimao Zhang ◽  
Shuhan Li ◽  
...  
Keyword(s):  
Data Acquisition ◽  
High Precision ◽  
Oil And Gas ◽  
Data Communication ◽  
Microseismic Monitoring ◽  
Acquisition System ◽  
Seismic Exploration ◽  
High Signal ◽  
Control Board ◽  
High Data

Abstract. In recent years, owing to the shortage of oil and gas resources and increased difficulty in mining, traditional (wired) microseismic monitoring equipment has been unable to meet the needs of energy exploitation. Therefore, it is necessary to develop new high-precision seismic exploration and data acquisition systems. In this study, we combined advance acquisition systems with wireless technology to develop a new wireless microseismic acquisition system. The hardware circuit of the acquisition system mainly included a data acquisition board and a main control board. High-precision analog-to-digital conversion and digital filtering technologies were used to provide data with high signal-to-noise ratios, resolution, and fidelity to the acquisition stations. Key technologies were integrated into the ARM of the main control board. Reliable GPS technology was employed to realize synchronous acquisitions among various acquisition stations, and WIFI technology was used to achieve wireless data communication between acquisition stations and the central station, thus improving the data transmission speed and accuracy. After conducting a series of evaluation tests, it was found that the system was stable, convenient to use, and had high data accuracy, therefore providing significant support for the solution to problems encountered in current oil and gas exploration processes, such as the complicated environment and inconvenient construction.

An optimization of the inverse scattering multiple attenuation method for OBS and VC data

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1293-1303 ◽  
Author(s):  
Luc T. Ikelle ◽  
Lasse Amundsen ◽  
Seung Yoo
Keyword(s):  
Free Surface ◽  
Data Storage ◽  
Inverse Scattering ◽  
Water Depth ◽  
Seismic Data ◽  
Computation Time ◽  
Ocean Bottom ◽  
Multiple Attenuation ◽  
Obs Data ◽  
Streamer Data

The inverse scattering multiple attenuation (ISMA) algorithm for ocean‐bottom seismic (OBS) data can be formulated in the form of a series expansion for each of the four components of OBS data. Besides the actual data, which constitute the first term of the series, each of the other terms is computed as a multidimensional convolution of OBS data with streamer data, and aims at removing one specific order of multiples. If the streamer data do not contain free‐surface multiples, we found that the computation of only the second term of the series is needed to predict and remove all orders of multiples, whatever the water depth. As the computation of the various terms of the series is the most expensive part of ISMA, this result can produce significant savings in computation time, even in data storage, as we no longer need to store the various terms of the series. For example, if the streamer data contained free‐surface multiples, OBS seismic data of 6‐s duration, corresponding to a geological model of the subsurface with 250‐m water depth, require the computation of five terms of the series for each of the four components of OBS data. With the new implementation, in which the streamer data do not contain free‐surface multiples, we need the computation of only one term of the series for each component of the OBS data. The saving in CPU time for this particular case is at least fourfold. The estimation of the inverse source signature, which is an essential part of ISMA, also benefits from the reduction of the number of terms needed for the demultiple to two because it becomes a linear inverse problem instead of a nonlinear one. Assuming that the removal of multiple events produces a significant reduction in the energy of the data, the optimization of this problem leads to a stable, noniterative analytic solution. We have also adapted these results to the implementation of ISMA for vertical‐cable (VC) data. This implementation is similar to that for OBS data. The key difference is that the basic model in VC imaging assumes that data consist of receiver ghosts of primaries instead of the primaries themselves. We have used the following property to achieve this goal. The combination of VC data with surface seismic data, which do not contain free‐surface multiples, allows us to predict free‐surface multiples and receiver ghosts as well as the receiver ghosts of primary reflections. However, if the direct wave arrivals are removed from the VC data, this combination will not predict the receiver ghosts of primary reflections. The difference between these two predictions produces data containing only receiver ghosts of primaries.

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