NO20200092A1

NO20200092A1 -

Info

Publication number: NO20200092A1
Application number: NO20200092A
Authority: NO
Priority date: 2020-01-24
Filing date: 2020-01-24
Publication date: 2021-07-26
Also published as: WO2021150121A1

Description

Compression and Transmission of Seismic Data

TECHNICAL FIELD

The present invention relates generally to compression and transmission of seismic data. More particularly, the invention discloses methods and systems for on-board compression of seismic data to an optimum level for a given loss of signal quality and then transmitting the compressed data to a cloud facility.

BACKGROUND

In seismic surveys, the seismic sensors collect seismic data about the subsea environment, which is then transmitted to the surface via communication network systems. Further, data acquisition units are deployed in the field proximate to the seismic sensors which are configured to receive signals from the seismic sensors, at least partially process the received signals, and transmit the processed signals to a remote unit or remote computer.

Onboard computing system typically controls the operations of the data acquisition units and may process the seismic data received from all of the data acquisition units and/or record the processed data on data storage devices for further processing and transmitting to a central control unit for further analysis.

In most of the seismic surveys, real-time access to the data for analysis and decision making may be necessary. The telemetry system (satellite communication or wireless communication etc.) is used for the measurement and transmission of data that is often collected by the data acquisition units for the purpose of real-time monitoring and analysis.

The extent to which data can be provided at a sufficient rate for real-time monitoring and analysis depends in part on how much data can be transmitted in a given bandwidth of the telemetry system. The current limitations of satellite communication do not allow the data to be transmitted to an onshore facility without compression as limited by the computing capability onboard the vessels and as a consequence we cannot use the most advanced algorithms to process the data in a timely manner.

Data compression is one method in which the amount of data transmitted in a particular time interval can be increased. The data compression methods are mainly divided into two categories: lossless (with no information loss) and lossy (leading to some information loss). Lossless compression allows the exact original data to be reconstructed from the compressed data. While lossy compression cannot reconstruct data identical to the original or the data reconstructed loses some part of the accuracy of the original data.

Also, in data compression, the higher the compression ratio, the higher the potential rate of data transfer is possible.

In real-time applications, in which the time between generation of data and the processing and receipt of the data should be as small as possible, computation complexity and delay costs often cannot be tolerated.

US patent No.10317544, US patent No. 10382842, US patent Application No. 16/027,408, US Patent No. 10349150, US patent No. 10200060 etc., disclose the seismic data compression techniques. These seismic data compression methods and systems are not able to reach sufficiently high compression ratios for the data. Furthermore, their computational complexity and delay cost is not tolerable in real-time applications.

Further, the seismic data from a survey is voluminous in nature, and typically has a substantial sampling rate. The need for efficient transmission is more acute in the case of wireless connections, which suffer from limited transmission bandwidth which makes timely transmission of rich data as one of the main problems. Seismic data compression can save a great deal of space in the mass storage modules in local acquisition units and/or local control, onboard system, and save a great deal of transmission time.

Therefore, there is a need of a method and a systemfor compression and transmission of seismic data to an optimum level for a given loss of signal quality and transmitting the compressed data to a cloud facility.

The disclosed systems and methods are directed to overcoming one or more of the shortcomings set forth above and/or other shortcomings of the prior art.

SUMMARY

Embodiments of the present inventions provide methods and systems for compression and transmission of seismic data to an optimum level for a given loss of signal quality and transmitting the compressed data to a cloud facility.

In one embodiment a method of compression and transmission of seismic data to a cloud is provided. The method includes determining optimum compression ratio for an accepted signal to noise ratio to reduce volume of the seismic data, obtaining highest level of compression using compression parameters optimization algorithm in tolerance iteration steps, performing compression of the seismic data, splitting the compressed data into two or more files, simultaneous parallel transmission of the compressed files to the cloud and cloud decompression at a remote surface.

In the embodiments, the method determines the maximum number of simultaneous transfers of compressed filed based upon network latency and storage seek throughput. Further, it may enhance use of the small bandwidth available for the transmission.

In one embodiment, the compression of the data is performed on the vessel using onboard system on the vessel. The onboard system comprises of a compression unit which receives seismic data and input arguments as an input, then it determines optimum compression ratio for an accepted signal to noise ratio to reduce the data volume as much as possible.

In another embodiment, a compression parameters optimisation is performed to determine the optimum compression ratio whilst retaining the ability to decompress the data to within specified criteria for degradation of the data. The compression parameter optimisation determines a set of compression parameters that just pass the data degradation test, allowing the maximum level of compression to be obtained whilst allowing the data to remain usable. One embodiment of this methodology is to start with high compression parameters and then incrementally reduce these until the level of degradation is acceptable. An alternative embodiment of this methodology would be to start with a nominal set of parameters and then adjust the parameters, either up or down, until the two sets of test parameters are as close as can be, one with just unacceptable degradation and one with just acceptable degradation. In each iteration of the above, or similar, methodologies the test data is compressed and then decompressed and compared with a reference version of the same data that has not been compressed and decompressed. The differences between the test and reference version of the same dataset are compared using some quality indicator, such as: mean square error, signal to noise ratio, peak signal to noise ratio in either / or both the time and frequency domains. A typical analysis in the frequency domain would calculate the mean trace by trace Fourier amplitude spectra for both the test and reference versions of the dataset. The difference between the test and reference version of the dataset is divided by the reference version of the dataset to get a signal to compression induced noise ratio. Commonly this would be limited to a pre-agreed frequency band and specified in decibels.

In some embodiments of the present invention, the iteration is repeated until the accepted degradation criteria is met and the compression parameters are recorded. After that full data is compressed using the compression parameters recorded above and a QA report is generated. Thereafter, if required, data file splitting is performed before transmission, and these split files are transferred onshore via the satellite link.

In some embodiments, the transmission of the compressed files is to maintain bandwidth to overcome the limitations of throughput for a satellite data link.

Further in some embodiments, the compression is performed prior to or during transmission to the cloud, that saturate the utilization of bandwidth efficiency by initiating right number of parallel streams.

Further in some embodiments, the compressed data is split into several files to run parallel transfers to overcome limitations of throughput for data transfers via a satellite data link.

Further in some embodiments, the system calculates the difference in volume between raw seismic data and decompressed seismic data.

Further in some embodiments, the system calculates the mean trace by trace Fourier amplitude spectra of the seismic data.

Further in some embodiments, the system calculates mean trace by trace Fourier amplitude spectra of difference between raw seismic data and decompressed seismic data.

In another embodiment, the present invention is a method of compression and transmission of seismic data from the vessel by electronic means, usually a satellite data link. The method includes onboard compression of the seismic data, transmission of the compressed files off the vessel, and decompression of the seismic data off the vessel.

In several embodiments, the compression includesdetermining optimum compression ratio for an accepted level of degradation caused by the compression algorithm to reduce volume of the seismic data, obtaining highest level of compression using compression optimization algorithms during compression parameter iterations, performing compression of the seismic data, and then, if required, splitting the compressed data into two or more files for transmission of the vessel.

For the onboard compression of the seismic data the system includes compression units configured for optimizing bandwidth usage and quality of transmitted data files.

The compressed file is then transferred from the vessel to the cloud, a remote server or similar, which are configured with decompression software.

In another embodiment, the cloud decompression includes joining the compressed files for realtime monitoring and analysis.

Other variations, embodiments and features of the present disclosure will become evident from the following detailed description, abstract and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The various features described herein will be best understood from the attached drawings, taken along with the following description, in which like numerals generally have been used to represent similar elements, and in which:

Fig. 1 shows a method of compression and transmission of seismic data of the present invention in accordance with an embodiment of the present invention;

Fig.2 shows flow chart representing a method of onboard compression of seismic data and a method of cloud decompression of compressed data in accordance with an embodiment of the present invention;

Fig. 3 shows flow chart of a method and algorithm of seismic data Compression optimization of the present invention in accordance with an embodiment of the present invention; and

Fig. 4 shows schematic diagram of Cloud data stream infrastructure of the present invention in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION

The present invention will now be described more fully hereinafter with reference to the accompanying drawings in which a preferred embodiment of the invention is shown. This invention may, however, be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, the embodiments are provided so that this disclosure will be thorough, and will fully convey the scope of the invention to those skilled in the art.

With reference with Figs.1 to 4, the present invention is described herewith in details. Embodiments of the present invention provide methods and systems for compressing seismic data to an optimum level for a given loss of signal quality and real-time transmitting the compressed data to an onshore cloud facilityfor the purpose of real-time or near to real-time monitoring and analysis.

In an embodiment of the present invention includes onboard compression of the seismic data to highest level, and then transmitting the optimized compression data to a location on shore.

Fig.1 depicts a flow chart of a method of compression and transmission of seismic data. The seismic data is received from the subsea environment using seismic sensors and data acquisition units of survey system. In one embodiment, the method includes a compression unit comprising of compression programs/ algorithms. The compression unit is also configured to perform operations on the data, prior to compressing and transmitting the data onshore. The operations may, in some embodiments, including finding the optimum compression ratio 102 i.e., compression 104 on the level of noise introduced by the operation usually measured as signal to noise ratio. The noise is the difference before and after compression. In other words, the noise ratio is comparing data from two or more data sets representing the same area and time before and after compression. This may increase the effectiveness of later-applied compression techniques.

In an embodiment, the method of finding the optimum compression ratio 102 before compressing data helps in compression optimization for a given loss of signal quality. The data is compressed at the highest level and then transmitted onshore. To ensure efficient transmission 106 of the compressed data, the compressed data is spilt into several files/parts/ packets to run parallel transfers to overcome the limitations of transmitting data over a satellite data link.

Further, in addition to parallel transfer, the method also proposes to saturate the utilization of bandwidth efficiency for the satellite data link by initiating the right number of parallel streams.

In the embodiments, the method includes transmitting the compressed data into files/ parts/ packets to the cloud and performs decompression 108 of the files/ parts/ packets at the cloud.

Once compressed, the data may be transmitted to the cloud into files/ parts/ packets by means of parallel transmission. The data transmission may proceed wirelessly, e.g., via radiofrequency transmission, or via any other suitable transmission medium. The data transmission may, for example, be into files/ parts/ packets to maintain bandwidth to overcome the limitations of throughput for a single SFTP/FTP over TCP.

At remote or at client location, decompression may decompress the data. The decompression may proceed as a complement to the compression algorithm used.

In one embodiment of the present invention provides Computation of the optimum compression ratio for a given signal to compression noise ratio. In some embodiments, simultaneous parallel transfers to saturate the available bandwidth compensating for inadequate bandwidth utilization for a single transfer due to latency.

In some embodiments, the remote computer receives the data stream and decompressed for realtime monitoring, analysis and interpretation.

The compressed data into files/parts/ packets occupies less than a bit length; and transmitting the plurality of files/parts/ packets to the cloud is achieved in timely manner. The transmitting of the compressed data may include transmitting the plurality of files/parts/ packets with a varying time interval between the transmissions. The time intervals may be computed using any technique that randomizes the time intervals, including a random number generator. The method may compute files/parts/ packets efficiency for each transmission before computing the time intervals between the transmissions of the files/parts/ packets and may transmit the files/parts/ packets without varying the time intervals when the files/parts/ packets efficiency is less than a certain threshold. On the cloud or at remote computer, a decompression unit receives the plurality of files/parts/ packets; decompress the compressed data; process the decompressed data and store in a data storage medium such as database. The decompressed data is then used for monitoring and analysis of the seismic data.

As mentioned above with reference to Fig. 1, the data is compressed prior to or during transmission to the cloud, which may saturate the utilization of bandwidth efficiency for a satellite data link by initiating the right number of parallel streams. In some embodiments, the method determines the maximum number of simultaneous transfers based upon network latency and storage seek throughput. Further, it may enhance use of the small bandwidth available for the transmission. Fig.2 illustrates a flow chart of a method for compression and transmission of seismic data in details. The compression of the data is performed at onboard system on the vessel. The onboard system comprises of a compression unit which receives seismic data 202a and input arguments 202b as an input 202, then determines optimum compression ratio for an accepted signal to noise ratio to reduce the data volume as much as possible. To determine the optimum compression ratio the compression parameter iterator 204 is performed. In the compression parameter iterator include compression parameter iterator definition 204a which is the criteria or algorithm to perform to determine compression parameters. For example, it may start with high values for compression parameters and gradually reduces the compression parameters in the small steps. For each iteration a decompressed version of data is created then calculates a difference between raw data and decompressed volume. Further the system calculates the mean of the trace by trace Fourier amplitude spectra of the data sample and also calculates the difference of the mean of the trace by trace Fourier amplitude spectra. As the compression parameters approach the optimum the compression induced noise level is reduced. In embodiments of the present invention, the iteration is repeated until the acceptable degradation criteria 206 is just achieved and chosen compression parameters will give maximum compression for a given degradation induced by the compression. After then full data 208 is compressed and QA report generation 210 is performed for the QA report 212. In the next step, a checksum 214a is created using a checksum calculator 214. Thereafter data file splitting 216, may be performed using split configuration 216a before transmission, where the splits files 216b are transferred to the on shore.

In another embodiment provides a method for onshore decompression. In the method for onshore decompression, either a single complete file or multiple split files 216b are received onshore along with the relevant onboard checksum 214a as input 218; and then split files 216b are joined together 217 if necessary. Thereafter, the checksum 214a is calculated and the checksum QC 220 is generated. In doing so, if the checksum QC 200 is failed then alert is generated and notifies the user about the errors 221, otherwise decompress 224 the checksum QC 220 to generate seismic data files 222. Further, a checksum is calculated 224 and the end user notified 226.

Some embodiments provide a method and an algorithm of seismic data Compression optimization as illustrated in Fig.3. As illustrated in Fig.3, the schematic diagram is Compression optimization algorithm of compression parameters iterator for obtaining highest level of compression. It starts with receiving full seismic data of the seismic survey, and then identifies a representative subset of this seismic data. After that the compression ratio and compression parameters are optimised. In some embodiments, further calculates the mean of the trace by trace Fourier amplitude spectra of the reference, uncompressed data sample and also calculate the mean of the trace by trace Fourier amplitude spectra of the of the test dataset that has undergone a compression / decompression cycle. This is then usually used to calculate a signal to compression-induced-noise ratio, often reported in decibels. Once the signal to compression-induced-noise criteria is met the compression ratio and compression parameters are said to be optimized for the agreed uponIn case the signal to compression-induced-noise criteria is not met, the compression parameters are adjusted and the process repeated until the signal to compression-induced-noise criteria is met and chosen value will give maximum compression for a given data of compression parameters.

In one or more embodiments, the methods described can be implemented in hardware, software, firmware, or any combination thereof, which may be located on the onboard subsea environment or remote station. For a software implementation, the techniques described herein can be implemented with units (e.g., procedures, functions, subprograms, programs, routines, subroutines, modules, software packages, classes, and so on) that perform the methods described herein. A unit can be coupled to another unit or a hardware circuit by passing and/or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, or the like can be passed, forwarded, or transmitted using any suitable means including memory sharing, message passing, token passing, network transmission, and the like. The software/ program/ algorithms can be stored in memory units and executed by processors. The memory unit can be implemented within the processor or external to the processor, in which case it can be communicatively coupled to the processor via various means as is known in the art.

In some embodiments, any of the methods of the present disclosure may be executed by an onshore data stream infrastructure system. Fig.4 illustrates an exemplary cloud data stream infrastructure system, in accordance with some embodiments. The system may include a computer, which may be an individual computer system or an arrangement of distributed computer systems. The computer system includes one or more database configured to store various program or data according to some embodiments, such as one or more methods disclosed herein. To perform these various tasks, the computer executes independently, or in coordination with, one or more processors, which is (or are) connected to one or more database. For the transmission for the file the system further includes software for transferring files such as but not limited to FileZilla client. Further includes a switch for transmitting over internet provided with firewall connected with network router (e.g. Marlink router) with communicates with satellite having landing station. The landing station further connected to telemetry system (teleport). The teleport is configured with a server for downloading or sharing the files from the server to the compression server for compression and transmission.

Further in some embodiments, the system is connected to a network interface to allow the computer system to communicate over a data network with one or more additional computer systems and/or computing systems, may or may not share the same architecture as computer system, and may be located in different physical locations, e.g., computer systems may be located in a processing facility, while in communication with one or more computer systems such as that are located in one or more data centers, and/or located in varying countries on different continents).

Further in some embodiments, a processor can include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.

Further in some embodiments, the storage database can be implemented as one or more computer-readable or machine-readable storage media. Storage media may include one or more different forms of memory including such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories, magnetic disks such as fixed, floppy and removable disks, other magnetic media including tape, optical media such as compact disks (CDs) or digital video disks (DVDs), BLURAY® disks, or other types of optical storage, or other types of storage devices.

Further in some embodiments, the system contains one or more compression unit and one or more cloud decompression unit may be used to perform some or all aspects of one or more embodiments of the methods. In alternate embodiments, a plurality of compression units and onshore decompression units may be used to perform some or all aspects of methods.

The foregoing description of embodiments of the invention has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed, and modifications and variations are possible in light of the above teachings or may be acquired from practice of the invention without departing from the scope of the invention. The embodiments were chosen and described in order to explain the principles of the invention and its practical application to enable one skilled in the art to utilize the invention in various embodiments and with various modifications as are suited to the particular use contemplated.

Claims

Claims:

1. A method of compression and transmission of seismic data to onshore, the method comprising:

determining optimum compression ratio for an accepted signal to compression-inducednoise ratio to reduce volume of the seismic data;

obtaining highest level of compression using compression optimization algorithm in compression parameter iteration steps;

performing compression of the seismic data;

optionally splitting the compressed data into two or more files;

parallel transmission of the compressed files to a remote onshore site; and

performing cloud decompression at the remote onshore site.

2. The method of claim 1, wherein the compression is onboard compression.

3. The method of claim 1, wherein the noise is the difference before and after the compression.

4. The method of claim 1, wherein the compression parameter iteration is repeated until a compression-induced-noise criterion is met and chosen value will give maximum compression for a given tolerance of compression-induced-noise.

5. The method of claim 1, wherein successive tolerance iteration is tightened or adjusted to reduce the compression-induced-noise level.

6. The method of claim 1, wherein the transmission of the compressed files to maintain bandwidth to overcome the limitations of throughput for a satellite data link.

7. The method of claim 1, wherein the compression is performed prior to or during transmission to the cloud, that saturate the utilization of bandwidth efficiency for the satellite data link by initiating right number of parallel streams.

8. The method of claim 1, the compressed data is, optionally, split into several files to run parallel transfers to overcome limitations of throughput for the satellite data link.

9. The method of claim 1, further calculates a difference in volume between raw seismic data and compressed seismic data.

10. The method of claim 1, further calculates the average of trace by trace Fourier amplitude spectra of the seismic data.

11. The method of claim 1, further calculates an average of trace by the trace Fourier amplitude spectra difference between raw seismic data and decompressed seismic data.

12. A method of compression and transmission of seismic data to onshore, the method comprising:

on-board compression of the seismic data;

transmission of the compressed filed to the cloud; and

onshore decompression of the seismic data,

wherein the compression includes,

iterating compression parameter optimisation for determining optimum compression ratio for an accepted signal to compression-induced-noise ratio to reduce volume of the seismic data,

obtaining highest level of compression using compression optimization algorithm by adjusting the compression parameters in iteration steps,

performing compression of the seismic data, and

optionally splitting the compressed data into two or more files,

wherein the transmission includes simultaneous parallel transmission of the compressed files to the onshore, and

wherein the onshore decompression includes joining the compressed files for real-time monitoring and analysis.

13. The method of claim 12, wherein the noise is the difference before and after the compression.

14. The method of claim 12, wherein the iteration is repeated until a measure of the compression-induced-noise criteria is met and chosen value will give maximum compression for a given set of compression parameters.

15. The method of claim 12, wherein successive tolerance iteration is tightened to reduce degradation noise level.

16. The method of claim 12, wherein the transmission of the compressed files to maintain bandwidth to overcome the limitations of throughput for the satellite data link.

17. The method of claim 12, wherein the compression is performed prior to or during transmission to the onshore, that saturate the utilization of bandwidth efficiency for the satellite data link by initiating right number of parallel streams.

18. The method of claim 12, the compressed data is split into several files to run parallel transfers to overcome limitations of throughput for the satellite data link.

19. The method of claim 12, further calculates a difference in volume between raw seismic data and compressed seismic data.

20. The method of claim 12, further calculates the average of trace by trace Fourier amplitude spectra of the seismic data.

21. The method of claim 12, further calculates an average of trace by trace Fourier amplitude spectra of difference between raw seismic data and decompressed seismic data.