Hindawi International Journal of Geophysics Volume 2018, Article ID 2913591, 8 pages https://doi.org/10.1155/2018/2913591

Research Article SEISGAMA: A Free # Based Seismic Data Processing Software Platform

Theodosius Marwan Irnaka, Wahyudi Wahyudi, Eddy Hartantyo, Adien Akhmad Mufaqih, Ade Anggraini, and Wiwit Suryanto Seismology Research Group, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara Bulaksumur, Yogyakarta 55281, Indonesia

Correspondence should be addressed to Wiwit Suryanto; [email protected]

Received 4 July 2017; Accepted 24 December 2017; Published 30 January 2018

Academic Editor: Filippos Vallianatos

Copyright © 2018 Teodosius Marwan Irnaka et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Seismic refection is one of the most popular methods in geophysical prospecting. Nevertheless, obtaining high resolution and accurate results requires a sophisticated processing stage. Tere are many open-source seismic refection data processing sofware programs available; however, they ofen use a high-level programming language that decreases its overall performance, lacks intuitive user-interfaces, and is limited to a small set of tasks. Tese shortcomings reveal the need to develop new sofware using a programming language that is natively supported by Windows5 operating systems, which uses a relatively medium-level programming language (such as C#) and can be enhanced by an intuitive user interface. SEISGAMA was designed to address this need and employs a modular concept, where each processing group is combined into one module to ensure continuous and easy development and documentation. SEISGAMA can perform basic seismic refection processes. Tis ability is very useful, especially for educational purposes or during a quality control process (in the acquisition stage). Tose processes can be easily carried out by users via specifc menus on SEISGAMA’s main user interface. SEISGAMA has been tested, and its results have been verifed using available theoretical frameworks and by comparison to similar commercial sofware.

1. Introduction Recently,alargenumberofopen-sourcesofwarepro- gramshaveemergedthatcanbeusedtoprocessseismic Geophysics is a branch of physics that studies physical refection data; however, each program has its own dis- properties of the earth, such as mass density, seismic wave advantages. For example, Seismic Un∗x[6]hasareally speed, electrical resistance, and magnetic properties [1–3] good ability to process seismic refection data, but it has from surface measurements. Tese physical properties can be no intuitive user interface and depends on a command-line further used to image subsurface geological conditions of the interface. Templeton and Gough [7] developed a web-based earth. One of the most popular methods in geophysics is the seismicdataprocessingtoolbasedontheSeismicUn∗x seismic refection method. Tis method is very sensitive to platform.Troughthiswebservice,userscanfll-outtheform a rock’s acoustic impedance variation, which is characterized provided by the server, and the input data will be queued by seismic waves refected in each interface of the subsurface on a parallel processing scheduler application. In this sense, layer or structure. Acoustic impedance is denoted by the the online service is a good concept, but the performance product of rock density and seismic wave speed within a is limited to user interaction via a form-based input with certain medium. Seismic refection is very popular, especially limited resources on the server side. DSISof, which was in the oil and gas industry, because this method yields high developedbyBeatyetal.[8],isaverticalseismicproflingdata resolution subsurface images of geological structures [4]. processor based on the MATLAB5 programming language. Te seismic refection method is also useful in engineering, MATLAB is a popular as programming language because environmental, geohazard, and ground-water exploration, as it has a library of common mathematical and engineering discussed by Steeples and Miller [5]. functions. Unfortunately, it has a large computational cost 2 International Journal of Geophysics as data size increases and is thus inefcient compared to a developed in this research consists of amplitude correction, lower level programming language (e.g., C, , and C#). muting, �-� and �-� domain transform, velocity analysis, A comparison between MATLAB and C, made by Andrews normal moveout (NMO) correction, and traces stacking. [9], shows signifcant speed diferences; He determines that a Tese processing steps combine into one trace with a high C program is up to 546 times faster than a MATLAB program. signal to noise ratio (SNR). A more comprehensive seismic refection data processing A more detailed explanation of the processing steps implementation in MATLAB was developed by Mousa and follows. Al-Shuhail, [10]. Another example is SEISPRHO [11], sof- ware developed in Lazarus Pascal Language, which can be 2.1. Amplitude Correction. Amplitude correction was per- used to interpret seismic refection and is enhanced with formed to compensate seismic signal weakening, which simple processing tools. Tis sofware is mainly developed for decreases exponentially as a function of time due to attenua- interpretation purposes. tion and geometrical spreading. Campillo et al. [20] explains Te recent popularity of Python, another high-level that this phenomenon ofen holds in some regional seismic programming language that is free and reliable, has many phases. Te phenomenon is also described by geometrical features to handle numerical problems and has high quality spreading [21]. Amplitude attenuation may be exploited via graphics. It is increasingly being used to develop geophysical an exponential or oscillatory equation; therefore, the ampli- data processing sofware [12, 13]. One of the advantages of tude correction can be formulated as an exponential equation Python is its ability to be installed on a server so that the appli- (1). �AGC is seismic data afer amplitude correction, �(�) is cation can be accessed remotely (e.g., [14]). Schwehr [15] has thedatabeforeamplitudecorrection,and� is an exponential developedanapplicationcalledseismic-py, which provides constant. Tis equation is an example of amplitude correction an infrastructure for creating and managing a Python library for a data-independent method. Afer amplitude correction, for each seismic data format. Rizvandi et al. [16] detailed the thesignalhasamplitudewithnoattenuationastherecording performance of an implementation of the Prestack Kirchhof time is increased. Time Migration in Python. Tere is currently no complete �� application that is built entirely with Python (i.e., ready to use �AGC (�) =�(�) � . (1) without combining the Python library to another library), as this would require specialized Python programming skills, at 2.2. Muting. Te muting process removes unused parts of least the basic ability to program in Python. the seismic recording. Tis process is very important because To the best of our knowledge, there is no other free in the seismic refection method, only the refection signal seismic refection data processing sofware program built will be considered, and other signals, such as those from with the C# programming language that has a complete direct waves, ground-roll, or refraction, must be removed. seismic processing toolbox, can process raw data from feld Te muting process is carried out by defning the area to be recordings, and includes an intuitive and appealing user removed frst, and then, SEISGAMA will automatically make interface. Te C# programming language was considered the amplitude of that region equal to zero. due to its native compatibility with the most popular oper- ating system, that is, Windows. Netmarketshare states that 2.3. �-� and �-� Transformation. Seismicdataistypically approximately 81% of desktop users have a Windows XP or represented in time-domain versus (range or) distance (�- newer operating system installed on their computers [17]. �). Te �-� transformation is carried out by using a 1D Te C# programming language is ofcially supported and Fourier transform and is applied to the transformation for periodically updated by Windows and included on a .NET each seismic trace in the data. Tis will transform the time (dot NET) platform [18, 19]. Developing applications natively series data into frequency domain data. Te results are then supported on Windows operating systems ensures long-term displayed in terms of distance (�-axis) and frequency (�- and continuous sofware development. Enhanced with an axis). Te Fourier transformation is expressed by intuitive user interface, SEISGAMA can easily be used by ∞ beginner or advanced users, and it is particularly useful −��� � (�) = ∫ � (�) � �� = �� (� (�)) . (2) for undergraduate geophysics students as they are learning −∞ processes. Te need for reliable and free seismic processing � � sofware has long been awaited, especially since the price Te - transform utilizes the 2D Fourier transformation to transform a time-domain version of each seismic trace of oil became variable. Tis sofware may ensure that oil 1/� explorationcanberesumedwithlowerassociatedcosts. into the frequency domain in andtransformthespatial domain of data into wave number (1/�). In this transfor- mation, seismic data in time (�) versus distance (�) will be 2. Methods transformed into frequency (�) versus wave number (�). SEISGAMA’s development is divided into several develop- Te 2D Fourier transform is an extension of the 1D Fourier ment sections: (1) basic data processing, (2) intermediate data transformation and expressed by (3) ∞ ∞ processing, and advanced processing. Tis paper reports −��� −��� only the basic processing aspects of refection seismic meth- � (�) = ∫ ∫ � (�, �) � � �� �� −∞ −∞ ods, and the advanced processing aspects will be discussed (3) separately in another paper. Te basic data processor that was = FT2D (� (�, �)). International Journal of Geophysics 3

2.4. Velocity Analysis. Te refection from a horizontal refec- 2.6. Stacking. Stacking is a process of merging many seismic torofaseismicwaveontherecordforaparticularseismic traces that are already in a state of zero ofset. Te stacking source will follow a parabolic equation process is done by quantifying the average amplitude of all signals (11). Tis stacking process is expected to improve SNR � 2 √� � (�) = √�2 +( ) . (4) (signal to noise ratio) to factor [10]. 0 V ∑� � (�) � (�) = �=1 � . (11) Tese characteristics are used to estimate the wave propaga- � tion speed by assuming the velocity of the medium. Parabolic response patterns can be detected using a shot-gather-based 3. Implementation seismic semblance calculation (��),asnotedbyMousaand Al-Shuhail [10]. SEISGAMA is written using C# programming language A seismic semblance is formulated as the quotient provided by Microsof Visual Studio 2015. Some scientifc between stacked and prestacked energy subsequently mul- computing functions and the display are implemented using tiplied by the number of seismic traces (7) for each time libraries from Ilnumerics Computing Engine and Ilnumerics � � window ( ). Time window parameters, with width ,are Visualization Engine [22]. SEISGAMA has a modular design �� � required to perform an calculation. Here, is the that aims to facilitate future development of the application. � � number of samples at the time window, ; is the number Some modules that are available in the application include � of the traces on seismic trace collections; �� is the amplitude the following: GamaseisProcessing and GamaseisView. Gama- � � at time and trace ; Es is stacked energy; and Eu is prestacked seisProcessing is on a SEISGAMA module that contains the energy. reading and writing data processing and some physics and 2 � � mathematical calculations of the seismic refection method. GamaseisView is a module that controls the graphical user Es = ∑ (∑��� ) , (5) �=1 �=1 interface, including windows, graphs, seismic sections, labels, and buttons. � � GamaseisProcessing consists of scripts to read data in = ∑ ∑�2 , Eu �� (6) a SEG-Y format, performing amplitude correction, muting, �=1 �=1 velocity analysis, normal moveout correction, and stacking. Es Te SEG-Y seismic data storage format is the most popular to NE = . (7) date, and it is used by almost all commercial seismic sofware. �×Eu Te reading function of the SEG-Y format is already sup- ported in any form; however, until now, this reading function 2.5. Normal Moveout Correction. A normal moveout (NMO) has been limited to two-dimensional seismic refection data. correction is carried out to restore the nonzero ofset seismic Other mathematical functions that have been included in refectors to zero ofset. Te correction is done afer we this program are implemented in accordance with existing obtain �0 and VNMO foreachrefectorduringvelocityanalysis theory. Calculation of Fourier transforms on SEISGAMA process. Te time delay afer NMO correction is defned in uses libraries that have been prepared and optimized by (9). A NMO correction is suitable for a refector having a ∘ Ilnumerics [22], which implements a special compilation slope of less than 15 . When a refector has higher slope than of C language functions to implement the algorithm called that threshold, another correction (Dip Move Out correction) the Fastest Fourier Transform from the West (FFTW) [23]. is required. Utilizing a premade library, which has been tested and uses Δ�NMO (�) =�(�) −�0, (8) a lower level programming language, is expected to improve the computation time of the Fourier transform. Tus, the �2 � � � � � (�) ≈ . calculation of the transformation to - and - domain is NMO 2 (9) 2�0VNMO mostly done using FFTW algorithm. GamaseisView consists of a set of views, views that govern NMO corrections can be categorized by three classifcations: the interface between user interaction with the sofware. (1) if the NMO velocity (VNMO)istoohigh,thenitwillhave (2) V Figure 1 shows the main user interface of SEISGAMA where ashapeofadownwardconvexrefector, if the NMO is users can perform seismic data processing easily. correct, then the refector will be fat on �=�0,and(3) if VNMO is too low, then the refector will be an upward convex refector. During this process, the NMO correction of seismic 4. Results and Discussion signals ofen causes a distortion in the frequency domain. To 4.1. Amplitude Correction. Amplitude correction was overcome this problem, a stretching factor (10) is a provision successfully implemented on SEISGAMA using a data- threshold that is required. If a signal is found to have a dependent exponential method. Users can change the stretching factor that exceeds the threshold, then a muting exponential constants �, but the program provides a default correction will be performed. value of �=16. Figure 2 shows the results of the amplitude Δ� (�) � (�) = NMO . correction using the implemented method. Te amplitude NMO (10) � = 2400 �0 of the refectors, which are associated with 0 ms, is 4 International Journal of Geophysics

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Figure 1: SEISGAMA’s main graphical user interface.

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Figure 2: Before (a) and afer (b) amplitude correction using SEISGAMA. not visible (Figure 2(a)), but it became clear afer amplitude waves became increasingly dominant compared to the correction (Figure 2(b)). Amplitude correction not only refected record afer amplitude correction. Furthermore, amplifes the signal but also increases the amplitude of the upon real seismic recording, noncoherent noise will also be noise. We can see in Figure 2(b) that refracted and direct amplifed afer amplitude correction. International Journal of Geophysics 5

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Figure 3: Muting process on SEISGAMA guided by white line (a) compared with muted shot-gather (b).

Offset (m) Wavenumber (k) 0 500 1000 1500 2000 2500 3000 −0.02 −0.015 −0.01 −0.005 0 0.005 0.01 0.015 0.02 0 0

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Figure 4: Shot-gather in �-� domain (a) and �-� domain (b).

4.2. Muting. In general, the response of the direct and which has been picked. Te results of the muting process can refractedwaveisassertiveandintrusivetoseismicsig- be seen in Figure 3(b), where waves other than the refection nals. Terefore, the muting process is necessary to remove response have been erased. responses that degrade or disrupt the signal. In SEISGAMA, the muting process is accomplished by picking the appropri- 4.3. �-� Dan �-� Transformation. Te transformation of ate unwanted points in the muting boundary (Figure 3(a)). seismic data from a �-� domain (time and distance) into Ten, the user is given a prompt to delete the top of the line the �-� and �-� domains can be seen in Figure 4. In the 6 International Journal of Geophysics

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Figure 5: Velocity analysis result (b) from shot-gather on (a).

�-� transformation, the vertical axis has been transformed Velocity into frequency units. From this display, we determine all of 1600 1800 2000 2200 2400 2600 2800 3000 frequencies included in each seismic trace. In the example, 0 the frequency content included on each seismic trace ranged between100and400Hz.Temaximumofthefrequency 500 axis is the Nyquist frequency. In this case, the maximum frequency is 1250 Hz; thus the sampling frequency is 2500 Hz. In the �-� transformation, frequency components for each 1000 seismictracearenotknowndirectly.Manymethodscan be performed in the �-� domain to determine specifc 1500 frequency of the trace; one example is to determine the apparent velocity of the incoming signal [24]. Time 2000 4.4. Velocity Analysis. In this section, we describe velocity analysis performed on the set of NMO uncorrected traces or 2500 on the imperfect NMO corrections. Trough analysis of the velocity, we can estimate the velocity of the medium which 3000 causes the parabolic phenomenon upon a refective seismic response. Users are prompted to enter several parameters that 3500 will be tested: that is, the width of the gate time, the minimum source wave speed, and the maximum source wave speed. Figure 6: Velocity picking from velocity analysis. Figure 5 shows the result of the velocity analysis applied to the fgure on the lef using the semblance seismic method. In this case, the user enters 25 ms as the time gate width, 1500 m/s as the minimum speed, and up to 3000 m/s as the NMO correction. A correct NMO correction, as shown, is maximum speed. Te results of the speed analysis are picked found by fattening seismic refectors. Figure 8(a) shows that based on the maximum values of the observed input for the the refector has become fat at times over 500 ms, while at NMO correction (Figure 6). timesbelow500msthevisibleconvexrefectorisstilldown, which means the velocity is still too high. 4.5. Normal Moveout Correction. NMO correction is per- formed using the previously chosen parameters used in 4.6. Stacking. In principle, the stacking process sums up all the velocity analysis. Velocity from the chosen result is the seismic traces to improve the signal to noise ratio (high associated with a linear relationship; therefore, the velocity S/N). Te stacking process can be carried out for any group is continuous each time. Figure 7(b) shows the results of the of seismic traces, but in the refraction seismic method, this International Journal of Geophysics 7

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Figure 7: Uncorrected seismic traces (a) and NMO corrected seismic traces (b).

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Figure 8: NMO corrected seismic traces (a) and stacked seismic trace (b). processmustbedoneafertheNMOcorrection,anditshould mic data for amplitude correction, muting, �-� and �-� be ensured that the refector is already fat; therefore the domain transform, velocity analysis, NMO correction, and stacking process really can improve the signal over noise. trace stacking. SEISGAMA was built using C# programming Figure 8(b) showed the stacking result from SEISGAMA language which is natively supported by a Windows operating sofware. system. A minimum .NET 4.5 framework is required to run this sofware; therefore, a minimum Windows 7 Service Pack 5. Conclusions 1 is implicitly required. SEISGAMA can give an alternative sofware choice to users interested in geophysics that has the SEISGAMA is a free seismic refection data processing added beneft of Windows’s compatibility and an intuitive sofware program that has successfully processed 2D seis- user interface. Te basic procedure for the processing of 8 International Journal of Geophysics

seismic data of refection has been implemented into SEIS- [13] L. Krischer, A. Fichtner, S. Zukauskaite, and H. Igel, “Large- GAMA. For advanced seismic processing option, including a scale seismic inversion framework,” Seismological Research Prestack Depth Migration and Full-Waveform inversion, this Letters, vol. 86, no. 4, pp. 1198–1207, 2015. is currently still under construction and will soon be provided [14] W. Suryanto and T. M. Irnaka, “Web-based application for in SEISGAMA. Te sofware is freely available upon request inverting one-dimensional magnetotelluric data using Python,” by contacting the authors. Computers & Geosciences, vol. 96, pp. 77–86, 2016. [15] K. Schwehr, “Seismic-py: Reading Seismic Data with Python,” Center for Coastal and Ocean Mapping,p.472,2008. 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