Seismic data processing

We  present  a  new  method  of  regularization  of  seismic
data using the finite offset common reflection source (FOCRS)  traveltime  approximation.  This method fits  curves
of common  reflection source to the reflection events and
stacks all the amplitudes in a given aperture. The stacked
amplitude, afterwards, is allocated to the time coordinate
in the trace to be interpolated. We applied this method to
three  synthetic  velocity  models  and  the  results  showed
the capability for regularizing  converted seismic waves in
stratified medium.

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The West Iberia Lithosphere and Asthenosphere Structure (WILAS) project densely covered Portugal with broadband seismic stations for 2 yrs. Here we provide an overview of the deployment, and we characterize the network ambient noise and its sources. After explaining quality control, which includes the assessment of sensor orientation, we characterize the background noise in the short-period (SP), microseismic, and long-period (LP) bands. We observe daily variations of SP noise associated with anthropogenic activity. Temporary and permanent stations present very similar noise levels at all periods, except at horizontal LPs, where temporary stations record higher noise levels. We find that median noise levels are extremely homogeneous across the network in the microseismic band (3-20 s) but vary widely outside this range. The amplitudes of microseismic noise display a strong seasonal variation. The seasonality is dominated by very-long-period double-frequency microseisms (8 s), probably associated with winter storms. Stacks of ambient noise amplitudes show that some microseismic noise peaks are visible across the whole ground-motion spectrum, from 0.3 to 100 s. Periods of increased microseismic amplitudes generally correlate with ocean conditions offshore of Portugal. Some seismic records display an interesting 12 hr cycle of LP (100-s) noise, which might be related to atmospheric tides. Finally, we use plots of power spectral density versus time to monitor changes in LP instrumental response. The method allows the identification of the exact times at which LP response changes occur, which is required to improve the understanding of this instrumental artifact and to eventually correct data.

The cross-calibration of different vintage data is an important prerequisite in attempting to determine the time-lapse seismic effects induced by hydrocarbon production in a reservoir. This paper reports the preprocessing and cross-calibration procedures adopted to modify the data of four seismic vintages (1982, 1989, 1992 and 1999) from the Oseberg field in the North Sea, for optimal conditions for a time-lapse seismic amplitude analysis. The final results, in terms of time-lapse variations, of acoustic impedance and of amplitude-versus-offset, are illustrated for selected data sets. The application of preprocessing to each individual vintage data set reduces the effects of the different acquisition and noise conditions, and leads to consistency in the amplitude response of the four vintages. This consistency facilitates the final amplitude cross-calibration that is carried out using, as reference, the Cretaceous horizon reflections above the Brent reservoir. Such cross-calibration can be considered as vintage-consistent residual amplitude correction. Acoustic impedance sections, intercept and gradient amplitude-versus-offset attributes and coherent amplitude-versus-offset estimates are computed on the final cross-calibrated data. The results, shown for three spatially coincident 2D lines selected from the 1982, 1989 and 1999 data sets, clearly indicate gas-cap expansion resulting from oil production. Such expansion is manifested as a decrease in acoustic impedance and a modification of the amplitude-versus-offset trends in the apical part of the reservoir.

In this paper, we present a new method of normal move-out (NMO) correction that works on a trace by trace bases technique rather than the current conventional sample by sample semblance analysis. The method corrects the pre-stack seismic data due to the NMO effect in both anisotropic and laterally heterogeneous mediums and simultaneously provides a full NMO velocity field that covers every single offset/azimuth in a common depth point (CDP). Also, we introduce a new computational method to recover the anisotropy effect from the extracted NMO velocity field. The method start by giving every single primary seismic reflector in a CDP, three different corrections; Positive correction (where the NMO velocity increases), Negative correction (where NMO velocity decreases) and zero correction (where NMO velocity doesn't change). The first two corrections (positive and negative) work only in case of anisotropy or laterally heterogenous mediums while the last correction is applicable in case of the layer is isotropic. Our method starts by picking the NMO velocity for each seismic reflector using the conventional semblance plot as an initial input to our method and since every seismic reflector has three different probabilities, getting all the possible combinations is crucial, and to get these combinations we simply use the combination with repetition mathematical method. To control the degree of the increasing and the decreasing of the NMO velocity, we use two parameters called the Anisotropy range parameter(A r)and its increment. The A r parameter is used to modify the NMO velocity of the primary seismic reflector N times based on the number of combinations. The total number of times where initial NMO velocities are modified is based on both the Ar parameter and the number of the seismic reflectors. Then, we use each of the modified NMO velocity traces (after the interpolation between the modified NMO velocities) to correct the corresponding seismic trace due to the NMO effect then, measure the similarity/semblance between the pilot trace (e.g. Zero offset trace) and that seismic trace under the NMO correction. This corresponding seismic trace is corrected due to the NMO effect N times and at each time we measure the semblance value. The modified NMO velocity trace that gives the highest semblance measure is selected. The process is repeated for all the other seismic traces in a CDP. We tested the method on different real and synthetic examples; Isotropic, anisotropic and laterally heterogeneous mediums synthetic examples are presented. Furthermore, we tested the method on a pre-stack CDP real example using Alaska dataset. The results show an excellent flattening to the seismic reflectors and provides a reasonably accurate normal move-out velocity field that covers every offset in a CDP.

Although Big Data is a trending buzzword in both academia and the industry, its meaning is still shrouded by much conceptual vagueness. The term is used to describe a wide range of concepts: from the technological ability to store, aggregate, and process data, to the cultural shift that is pervasively invading business and society, both drowning in information overload. The lack of a formal definition has led research to evolve into multiple and inconsistent paths. Furthermore, the existing ambiguity among researchers and practitioners undermines an efficient development of the subject. In this paper we have reviewed the existing literature on Big Data and analyzed its previous definitions in order to pursue two results: first, to provide a summary of the key research areas related to the phenomenon, identifying emerging trends and suggesting opportunities for future development; second, to provide a consensual definition for Big Data, by synthesizing common themes of existing works and patterns in previous definitions

The study is focused on the formation evaluation of Srikail gas field located in western part of folded belt of the Bengal Basin which can be used to improve reservoir characterization. Digital version of wireline log data is used in this research work. Data analysis is done to evaluate the reservoirs using Techlog 2011 software. Four wells are drilled and data are used in the identification of prospective zones and determination of petrophysical properties and hydrocarbon presence. Seven hydrocarbon bearing zones within the measured depth range 2429.5-3501 m with volume of shale ranging from 8%-38% are interpreted. The effective porosity of the reservoirs ranges from 12.3%-24.9%, indicating the reservoirs have moderate to good porosities. The ratio of the net to gross thickness of the reservoir ranges from 10%-56%, while the water saturation ranges from 24.9%-46.9%. From the water saturation deductions, the hydrocarbon saturation ranges from 53.1%-75.1% of gas in the reservoirs indicating all the zones well saturated with hydrocarbon. From gross thickness, net thickness and net to gross ratio it is found that D, E and F sands have the significant gross and net thickness and net to gross ratio among the gas sands. Hence the three gas sands have comparatively higher reserve than the other four gas sands (A, B, C and G sands). Finally well to well correlation is done which reveals the detailed picture of reservoir sand distribution of Srikail gas field with the reason of missing of reservoir gas sand in the Srikail-1 well.

To remove some of the ambiguities in a heterogeneous oil reservoir, a three dimensional model of the reservoir would be constructed by application of newly introduced methods. The aim of this study is to define an accurate and efficient model of a complex reservoir in southwest of Iran and accurately derive the geological and geometrical properties of the reservoir for well location proposal. Seismic data in addition to well logs were used for that purpose. A corner point grid was used in this study, and a generic global scale-up method was combined with previous result for reservoir simulation. The final model pointed out the heterogeneous characterization of the reservoir and proved the advantage of combining these methods in constructing accurate and efficient reservoir models. According to these models, it is concluded that the reservoir has different productive zones in different members that was not cleared in the previous models.

(In English) The strong and felt earthquake with magnitude 6.5 occurred in 119 km to the southeast of Cilacap Regency, Central Java Province at a depth of 48 km. The earthquake centered on the sea at coordinates 8.48o latitude and 109.17o east longitude on January 25, 2014. The earthquake triggered damage in several locations, including the districts of Banyumas, Kebumen, Cilacap and Purworejo. In order to mitigate natural hazards, this study aims to determine the relationship between seismic wave velocity and depth of layers near the surface in shallow geological structures. The method used in this study is the seismic refraction method. This method is done by interpreting seismic signals from man-made waves that spread near the surface of the earth. The seismogram will display the travel time of the waves, the distance between the waves and the source of the waves themselves. The structure of the geological layers that exist in the earth can be estimated based on the magnitude of the seismic wave velocity. This research is located in the campus area of the Indonesian Institute of Sciences Karangsambung. Measurements were made considering its location close to the center of the earthquake and the uniqueness of the rock formed by the removal of the ocean floor. Based on the results of the study it is known that there is a relationship between seismic wave velocity and the depth of the layers near the surface. The deeper the layer of soil from the earth's surface, the seismic wave velocity will be higher.

Keywords: seismic; refraction; geo-hazard; soil property

(In Bahasa) Gempabumi kuat dan dirasakan dengan kekuatan magnitudo 6.5 terjadi di 119 km ke arah tenggara Kabupaten Cilacap, Propinsi Jawa Tengah pada kedalaman 48 km. Gempabumi tersebut berpusat di laut pada koordinat 8.48 o LS dan 109.17 o BT pada tanggal 25 Januari 2014. Gempabumi tersebut memicu dampak kerusakan di beberapa lokasi, termasuk kabupaten Banyumas, Kebumen, Cilacap dan Purworejo. Dalam rangka mitigasi bahaya alam kebumian, maka penelitian ini bertujuan untuk mengetahui hubungan antara kecepatan gelombang seismik dengan kedalaman lapisan-lapisan dekat permukaan pada struktur geologi dangkal. Metode yang digunakan dalam penelitian ini adalah metode seismik refraksi. Metode ini dilakukan dengan menginterpretasi sinyal seismik dari gelombang buatan manusia yang menjalar di dekat permukaan bumi. Seismogram akan menampilkan waktu tempuh gelombang, jarak antar gelombang dan sumber gelombangnya sendiri. Struktur lapisan geologi yang ada di dalam bumi dapat diperkirakan berdasarkan besarnya kecepatan gelombang seismik. Penelitian ini berlokasi di area kampus Lembaga Ilmu Pengetahuan Indonesia (LIPI) Karangsambung. Pengukuran dilakukan mengingat lokasinya yang dekat dengan pusat gempabumi dan keunikan batuannya yang terbentuk dari pengangkatan lantai dasar samudra. Berdasarkah hasil penelitian diketahui bahwa terdapat hubungan antara kecepatan gelombang seismik dengan kedalaman lapisan-lapisan dekat permukaan. Semakin dalam lapisan tanah dari permukaan bumi, maka kecepatan gelombang seismik akan semakin tinggi.

Kata kunci: seismik refraksi, bahaya kebumian, sifat tanah

We have used on- and offshore seismic reflection profiles to determine the extension of a historic landslide at depth and toward the sea. The subsurface landslide structure was delineated by using four separate data sets produced by the combined use of geophone and hydrophone spreads, and of explosive and air-gun sources which also illuminated, through an undershooting configuration, the subsurface below the coastal road and railway.Many noise problems related to the source and environment were overcome and alleviated with several signal-processing routines. The resulting stack and depth-migrated sections reveal the deep geometry of the main landslide body and indicate the emergence location, at the landslide foot, of a deep, potential detachment surface, which previous investigations failed to evidence.

The development of carbonate reservoir characterization has evolved rapidly. One newmethod that is currently in use is Common Contour Binning (CCB). CCB is new technology whointroduced by using the concept of amplitudestacking of seismic 3D post stack data. CCB is usedto detect subtle hydrocarbon-related seismicanomalies and to pinpoint gas-water, gas-oil andoil-water contacts.The method enhances an amplitude anomaly todetect the oil water contact and compares it with a back propagation neural network to determine thedensity distribution. The density distribution fromthe back propagation neural network is used tosupport the results of common contour binning.In this paper, we assume that the oil water contact islocated at the interface of two contrasting densitylayers. In this case, the hydrocarbon trappingmechanism is a fault trap. Initially, the fault wasidentified using a fault enhancement filter, other seismic attributes were used to estimate the probability of an oil water contact in the reservoir.Common contour binning was then applied. Theinput data for the back propagation neural network  process are seismic attributes that have a goodlinear correlation with the petrophysical data fromthe target, in this case density data from five wells.The procedure indicates a combination of the twomethods yields good oil water contact predictionsfrom 3D post stack seismic data