فصلنامه فیزیک زمین و فضا
سال سی و نهم شماره 4 (زمستان 1392)

Gowk fault which is located west of the Lut-block east of Iran is one of the main and active structures in the region. To estimate the activity of this fault, we need to calculate its’ slip rate. The South part of the Gowk fault passes through the Golbaf Lake and has displaced the rivers which have cut the lake. The displacement is around 30 meters and if we can find the time of displacement we can then calculate the slip rate. One of the most useful methods to date the Quaternary sediments directly, is Luminescence dating. This method has been widely used and the range of materials that can be dated, using different procedures of luminescence dating, is being developed. In this paper, we are presenting part of the research which was done to sort out the problems that we had for dating the samples that were collected from the Golbaf lake. To measure the age of the samples, two parameters are needed; the equivalent dose and the dose rate. To determine the equivalent dose, the single aliquot regenerative dose (SAR) protocol was used. In this method, after measuring the natural signal, the sample is exposed to different known doses in the laboratory and the related luminescence signal is measured. Then, a standard growthcurve is built, which the equivalent dose can be calculated from. To examine the suitability of the SAR protocol in dating the collected samples, the capability of this method in order to recover a known laboratory dose was investigated. We confronted some unexpected results while recovering the dose because the determined dose overestimated the certain given dose in the laboratory by around20 percent. Three possible reasons were considered: methodological factors which can influence the determination of the equivalent dose, physical processes affecting the luminescence signal and technological factors(the measurement device).The first two reasons were assessed experimentally (according to tables 1 and 2). Thirty aliquots were built from the GB3 feldspar sample and the Risoe automated TL/OSL DA-15 reader was employed for all experiments. The first 15 aliquots were used for determinations according to the left column in table1 (the cut heat is fixed). The natural signal was depleted and after 10 hours gap, the signal was measured again (Figure1). Then, all samples were exposed to 26 Gy dose (assuming as the natural dose), the procedure in the left hand side of table1 was followed to test the capability of SAR in recovering this dose. In table1, Lx shows Ln (natural luminescence signal) and LR (regenerative luminescence signal) and Tx shows Tn (natural test dose signal) and TR(regenerative test dose signal).The results in figure2 demonstrate that, the recovered dose is more than the given dose by approximately 20% (about 30 Gy).After that, the same procedure was followed for the next 15 aliquots according to the right column of table1, but with equal preheat and cutheat. The results are shown in figure3 which is the same as figure2.We then repeated one stage of the SAR protocol five times for each aliquot using a fixed dose and expected that the results for all to be similar. This stage was completed according to table2 for four aliquots. The results are shown in figures 4, 5 and 6. As is shown in figure 4, the first signal consists of more photons in comparison with the other signals. Figure 5 shows the regenerative dose and the test dose curves for the four aliquots in five cycles. As is clear in the diagram, the first point of the regenerative dose curve for all the four aliquots are more than the other points in the curve, for both IR and Post-IR methods. Figure 6 shows the Lx/Tx ratio. It can be explicitly seen that the first stage is 40% more than other stages. As all the luminescence signals following the test doses (Tx) are almost similar, this 40% difference cannot be due to sensitivity change. The above experiments show that electron exchange from heat-sensitive traps to light-sensitive ones because of the preheat effect cannot be the reason for the dose recovery overestimate, since both IRSL and OSL signals measured 10 hours after natural measurements, are negligible in compare to natural signals. Electron exchange from the light-sensitive traps to the heat-sensitive ones due to laser light and subsequently in the opposite pattern cannot be a possible reason since all the standard growth curves pass through the origin (figure 7).Incomplete evacuation of the electrons because of inadequate intensity and time of the laser beamis not responsible for the dose recovery overestimate because laser beam has been similar for all the stages through the experiments. Inability of the SAR protocol to correct the sensitivity according to heat, dose and light is not the case since the SAR method has provided almost similar result for the last four stage of figure 6. As the methodological and physical factors could not be the reason for overestimating the recovered dose in the laboratory, we focused on the third factor, technology. Although the device (TL/OSL DA-15 reader) is claimed to be complete and without any defect, some reports of its failure has been presented. The effect of the dose and light on adjacent aliquots as reported by Bray et. al (2002), was found to be responsible for dose overestimation. This is because of the packed arrangement of aliquots on a disk. Since we wanted to investigate and eliminate the possible effect of the radioactive dose and the laser beam on adjacent aliquots, we decided to rearrange the aliquots. So the same procedure presented in tables 1 and 2 was followed for aliquots 1, 4, 7, 10 and 13. The results have been shown in figures 10 and 11. Figure 10 shows the result of repeating a cycle for these aliquots. This figure demonstrates that there was not much sensitivity change for the sample in this case. Figure 11 shows that the SAR method was capable of recovering the dose properly at different temperatures, but 2400 and 2800 are the most suitable temperatures in this case. So the problem was solved by putting the aliquots in every two other positions, and the SAR protocol could recover the given dose properly. We repeated this procedure by setting the aliquots in every other position too and the results were the same. Based on above result we put the natural aliquots in every other position and determined the age of the GB3 sample. This procedure provided an age of 4100 years for this sample. Similar approach was considered for calculating the age of other samples from the same site. Detailed information about the process of dating and the slip rate of Gowk fault could be found in the paper ‘Determination of the slip rate on the Gowk fault’ by Fattahi et al. (submitted).

Earthquakes usually occur not as separate individual events, but they usually constitute parts of an earthquake sequence with different but defined characteristics. Earthquake swarms include earthquake sequences, which start gradually and end gradually with no dominant earthquake in the sequence in terms of magnitude. Study of earthquake swarms of the world has started from about half a century ago. The first stages of these studies suggested that earthquake swarms are closely related to volcanic regions, and upwelling of pore fluids. It was also suggested that this kind of sequences occur in regions with strong strength gradients. Non-double-couple focal mechanisms are reported to be associated with earthquakes in geothermal regions and with earthquakes related to tensile faulting resulted from pore pressure in geothermal or volcanic areas. Some other various subordinate settings are also suggested for earthquake swarms. They include settings related to geothermal regions, thrusting, releasing stopovers, pull-apart basins and mud volcanoes. Some earthquake swarms are suggested to be triggered by a distant major earthquake in distant regions. Most of earthquake swarms are not accompanied by surface ruptures; however some exceptions have been reported from California in United States. Due to their relatively small magnitudes, the earthquake swarms have been less considered by researchers in Iran, although some of them have caused damages and destructions. This research studies 24 events of earthquake swarms that have occurred during the historical and instrumental periods of seismic activity in Iran, and tries to investigate their general characteristics and geological settings. The earliest accounts of a historical earthquake swarm in Iran probably dates back to 1482 A.D., when a sequence of foreshocks jolted the western Makran region in southeastern Iran for about 3 months; the earthquakes culminated in a destructive earthquake of 1483 A.D. in Hormuz Straight. Two sequences of earthquakes in 1819 and 1856 A.D. caused destruction in the Tabriz region of northwestern Iran. One of the deadliest earthquakes in Zagros region (Qir-Karzin earthquake of 1972, Ms=6.9) was preceded by a sequence of small and moderate earthquakes which had started about one month earlier. Results of this research indicate that most of the earthquake swarms in Iran occur in Zagros (54%), then in southern central Alborz (17%) and Azarbayjan (17%) areas. The rest are observed within Central Iran, Makran and Eastern Iran. It is interesting that despite their seismotectonic activity, the Eastern Iran and Kopeh-Dagh regions are not associated with important earthquake swarms. This may be related to a rather continuous seismogenic layer as compared to other parts of the Iranian Plateau. Earthquake swarms in Iran are observed both independent and related to the larger main shocks. Duration of occurrence of the earthquakes depends on to the general size of their magnitudes, and varies between 2 days for earthquakes smaller than 2.3 to more than a year. The longest sequence in Iran occurred after the Western Marivan earthquake of 1946, which lasted for 398 days. Number of reported events within an earthquake swarm sequence varies between 6 and 236, and even reportedly 1200. Size (diameter) of the epicentral region in which earthquake swarms occur varies between 12 and 146 km. None of the studied events in Iran, even those close to the volcanic regions, show any clear relationships to volcanic activities or upwelling of pore fluids. The only exception may be the Arak earthquake swarm of 2012, where thermal spring in the region may suggest some relationships with upwelling of pore fluids. The b value for the events in the Arak area does not deviate very much from 1, despite the early suggestions by some researchers of values greater than one for earthquake swarms. Spatial distribution of the Arak sequence does not conform to any planar (tectonic) structure at depth. Depth distribution of the earthquake swarms in Iran indicates that all of them have occurred within the crust. We suggest detailed study of focal mechanisms for the events in earthquake swarms of Iran to discriminate events related to earthquake faults from those which may be related to fluid injection at depth. In some regions, such as Zagros, earthquake swarms may be related to the mechanical discontinuities within the crust. Statistical analysis of earthquake swarms in Iran indicates that the cumulative magnitude of earthquakes within a sequence does not exceed more than 0.5 unit over the largest event of the same sequence. Statistics on magnitude, number of events, spatial and temporal distribution characteristics of the earthquake swarms in this study provide a ground on which seismologists may investigate this type of seismic activity in more details, and discriminate between the earthquake swarms and mainshocks or foreshokes.

A seismic survey in a geothermal site near the Karlsruhe city in Rheine river graben in Germany was performed to provide a detail map of structures for geothermal usage of that area. The geothermal site uses the enhanced geothermal system (EGS) for power generation. The EGS system needs a hot dry rock (HDR) in depths with a spread system of faults and cracks. An injection well, injects the surface water to the fractured hot rock and water pass through the fractures and faults and becomes hot. Then two pumping wells will pumps up the hot water to the surface. One of the pumping well in that site did not perform with efficiency that was planned for. The problem might be due to the impermeable rock between injection well and pumping well in that part of the hot rock. Therefore mapping the faults, major or minor ones, and the boundary of the layers is an important task in that project. It should be mentioned that before the surface seismic project, a vertical seismic profiling (VSP) was performed in that well that due to the high temperature in well, the receiver sounding devise was failed and no data was gathered. The second VSP project even with thermal resistant devise was also failed. Therefore obtaining a reasonable seismic image of that part was so critical for stopping or continuing the geothermal activities there. Then a surface seismic project was planned with two 2D seismic lines. However, seismic imaging in such faulted regions is among the crucial task by conventional methods. The CMP stack followed by DMO and post stack migration and prestack depth migration (PSDM) were both performed on the data. Result of the conventional post stack time and depth migration was not so ideal that interpreter could trace the minor faults on the final section. PSDM method also needs an accurate velocity model that would be obtained by so much effort. However, the prestack depth migration was carried out and faults could be traced in that section. However, the seismic image has some ambiguities in interpretation and the velocity model was not fully trustable. Therefore it was needed to use new imaging method for seismic imaging in such media. The common reflection surface (CRS) stack is among the new methods for seismic imaging. It has some advantages that make it usable for imaging in such regions. It is also independent from macro velocity model. Therefore, accuracy of the velocity model is not a big concern here. The CRS stack method also gives three kinematic wavefield attributes that could be used for further interpretation. These attributes relates to the dip, curvature and depth of the reflector. The best advantage of the method is that it gives an enhanced section for migration correction. The CRS stack method use a higher order of traveltime equation rather than the CMP stack method. Therefore the CRS stack operator works on a surface in time domain rather than on a trend. These properties make the CMP stack method a special case of the CRS stack method. Moving to a higher order traveltime equation will dramatically increase the signal to noise ratio in the final section. Höcht (1998) derived equations that give the traveltime of ray by kinematic wavefield attributes, known as CRS equation. In his calculation, the second order of travel time for t2, is known as CRS stacking operator: (1) where RNIP, RN and α are CRS attributes, V0 is the near surface velocity and X0 is the point of the emergence of the central ray. As it could be seen from the equation, this equation does not need any information about the velocity model of the subsurface, and only knowing the near surface velocity would be enough. Then the CRS stack method was performed on the data. The result of the CRS stack method was comparable to the result of PSDM. It should be noted that in the CRS stack method, an accurate velocity model is not necessary and the final section has better quality. However, in the CRS stack processing chain, mapping the position of faults was difficult due to the problem of conflicting dips that exists at the end points of faults. Therefore a new method was developed here designed especially for imaging the faults or any type of discontinuity in the reflectors, while preserves advantages of the CRS stack method. To achieve this goal, the idea of diffraction stack migration in Kirchhoff migration was used to modify the CRS stack operator. To have an idea about how the CDS operator works, consider a segment of a reflector in a predefined position in zero offset (ZO) section. This segment would be defined by its related wavefield attributes on that point. Now consider a hypothetic diffraction point exactly at the same point (in the middle of the segment). The ray path for diffraction and reflection in that point would be the same for both situation and the traveltime and emergence angle are the same, too. In the literature of the CRS stack method; we can see that the parameter RNIP is independent from the curvature of the reflector in the point of imaging. Soleimani and Mann (2008) proved that the Kirchhoff migration operator is a special case of the CRS operator with RNIP=RN. In other words, if the CRS stack operator for an arbitrary reflector segment is known, an approximation of the associated Kirchhoff migration operator is readily available by substituting RNIP for RN in equation. To perform diffraction stack migration on the CRS stack method, the operator should switch from reflection response to diffraction ones. Therefore the method could be called common diffraction surface (CDS) stack method. The new introduced CDS operator will gather all of the diffracted energy in the data. The CRS stack method gives the priority to the most coherent event for producing the operator in (xm,t,h) space and will have only one stacking surface, while the CDS stack, does not put any criteria for selecting the surfaces. Otherwise there is a risk to lose a relatively weak diffraction that is masked by strong reflection. Thus, there would be no image of the geological phenomena that was responsible for that lost diffraction in final migrated section. It is the reason of not imaging faults or discontinuity in the layers in most of the seismic imaging method. To preserve all diffraction shown in (xm,t,h) space, there would be as many as operators according to the number of diffraction in that space. To switch CRS stack traveltime to the diffraction CDS stack, the following combination between two kinematic wavefield attributes was considered and the new attribute (RCDS) was derived: (2) where. The new introduced method was applied on the data. Like as the conventional method, the first section obtained in the processing chain was the stacked section by CDS method. In the CDS stacked section, the quality of the section was not improved well. However, as it was mentioned, the advantage of this method would be clearer in the migrated section. In the next step, all the stacked sections obtained by the CMP, CRS and the CDS methods have been migrated by the Kirchhoff post stack depth migration. In the migration section that was obtained by migration correction on the CDS stacked section, more reflection events and more faults were imaged with better quality. In comparison to the post stack time migration on conventional method and CRS stack method, the CDS stack operator even with a smooth velocity model could gather more diffracted energy for imaging than the other migration operators. The final CDS migrated section is of a better quality and contains more detail about the location of the minor faults. The result of this migration is also comparable with the PSDM result. In some cases, the new method could image faults better than the PSDM result. It should be mentioned that the post stack depth migration applied on the CDS stacked section, needs only a smooth velocity model that would be easily obtained. With detail geological interpretation on this section, the results show that the region contains many small faults that transfer the pumped water from injection well through the hot rock to the steam extraction well.

Discrete Fourier Transform (DFT) is the basic part of various algorithms of signal processing in many fields of science and technology. For analysis of signals with DFT, the length of discrete signal must be finite so signal to be analyzed must be divided to some windows. Consequently, spectrum leakage appears in frequency domain. Energy leakage of DFT spectrum can also occur due to non-uniform sampling in time or spatial domain and usually is more serious. The leakage can hide smaller spikes among actual spectrum and is an important factor that affects spectrum estimation. In practice, we should try to reduce the energy leakage of DFT spectrum to improve the resolution of frequency spectrum. For evenly sampled signals, suppressing approaches of spectrum leakage are diverse; most common method among them is windowing method. Study on how to suppress spectrum leakage of non-uniform Fourier transform is important both in theory and practice. Here we introduce and apply an anti leakage Fourier transform (ALFT) algorithms for suppressing spectrum leakage of non-uniform Fourier transform, improving the resolution of temporal frequency spectrum or spatial wave number spectrum. One of the areas of study that has the same problem is seismic exploration technology. Seismic data sets are generally irregularly sampled in inline midpoints, cross-line midpoints, offset and azimuth. This irregular sampling can limit the effectiveness of high end 3D de-multiple and imaging algorithms such as 3D surface related multiple elimination, wave equation pre-stack depth migration and many other processes. To overcome this issue, it is common in seismic data processing to use regularization and interpolation. Interpolation processes fill the missing traces and regularization transfer traces from their irregular recorded location to locations on a regular grid. We apply ALFT for seismic data interpolation and regularization that leads to reconstruction of seismic data on a regular grid. ALFT is an iterative algorithm that acts on frequency slices and reconstruct each temporal frequency spectrum along spatial dimensions. For an input data with N_p known samples, the original algorithm of ALFT can be performed as follow: 1- Computing Fourier components of the data using equation 1. (1) 2- Selecting the largest coefficient and adding it to the precomputed coefficients. 3- Updating data by subtracting the contribution of selected coefficient (equation 2) from input data (equation 3). (2) (3) 4- Iterating steps 2 and 3 until reaching the threshold. The idea of ALFT is simple and intuitive: first seismic data will be transformed to f -x domain, by applying DFT the f -k spectrum of data will be estimated. The largest Fourier coefficient is selected and subtracted from the input data. In the subsequent iterations, successive maximum components are subtracted until the norm of the residual is negligible. This iterative processes is able to recover a sparse spectrum that, when evaluated at sampling points, approximates regularly sampled data. This method relies on the common assumption that sparsely sampled data can be represented by a few Fourier components. ALFT can handle pure non-uniform seismic data and uniform seismic data with gap and missing traces. For regular data sets, by applying an anti-alias mask ALFT can handle steep dips. Generalization of ALFT to higher dimensions is simple and straightforward and for high dimension data ALFT can reconstruct very sparse data sets. Performance of the method was tested on both synthetic and real seismic data. We applied ALFT algorithm to reconstruction of synthetic and real seismic data sets. The results show the effectiveness of ALFT in interpolation and regularization of input data on any desired regular sampling grid. Compared to those interpolation methods that use FFT, ALFT has a slow procedure. However, computing the DFT’s in small windows of data sets, greatly reduces the computational cost of the algorithm. On the other hand, when the input data sets are sampled on a regular grid which has missing traces or gaps, one can use FFT instead of DFT to compute Fourier transform. ALFT reconstruction method suffers much less from edge effects and gibs phenomenon. The sequence of computing Fourier coefficients from maximum energy to minimum energy, and subtraction of contribution of them from remained data, plays a key rule in ALFT algorithm.

Considering this fact that chromite masses possess high density, the gravity method is the most common geophysical method suggested for prospecting of chromite deposits. Usually, the result of superposition of several factors is observed in the acquired datum, which includes different spatial scales. The observed potential field could be assumed as the sum of the regional field, the residual field, and noise. Despite filtering out several factors to obtain a bouguer anomaly map from gravity survey data, the obtained values are still the result of superposition of several components; these components are different from the view points of scale and importance. Definition and recognition of these components are essential in interpretation of geophysical surveys. There are various methods for processing and interpretation of bouguer gravity anomaly maps. These methods, e.g. potential field filters, are mostly based on mathematical analyses using trial and error technique. There are many different methods concerned with separation of the regional and residual components from the gravity map. Upward continuation technique is frequently used to identify regional anomalies and gravity variations of deeper recourses. The upward continuation is a general filter in processing geophysical data that can remove or considerably lessen the contribution of high-frequency, near-surface, shallow causative bodies from the gravity field, resulting in a smooth field reflecting the deeper causative bodies and/or density structures. This method is applied to separate a regional anomaly from the observed gravity. This filter is a low pass filter since the residual component, which is concerned with local anomalies, can be assumed as high frequency part of the signal. The main weakness of usual potential field filters comes from the fact that they cannot take into account spatial structure of components while filtering them. Spatial structure of a variable is an indicator of the amount of data correlation with respect to the distances between the data. Factorial Kriging analysis (FKA) is principally a geostatistical filtering method that includes classic factorial analysis and geostatistics. The FKA method consists of three basic steps: variogram, factorial analysis and Kriging/co-Kriging. This method computes of the experimental variograms to choose the number of spatial scales to be considered and fit by theoretical models, (generally linear model of regionalization/coregionalization), applies the decomposition method on variance-covariance/variogram matrix of spatial components (generally principle component analysis/spectral decomposition), estimats the regionalized factors in order to determine the relative contribution of each factor for the estimation of a particular location and mapping. Factorial Kriging decomposes the raw variable into as many components as the identified structures in the variogram. The basic step in FKA is experimental variogram calculation and fitting a valid model to this variogram. If the variogram is nested, it can be represented as a combination of several individual components variograms. The FKA method includes two types of univariate and multivariate. In the case of a geophysical variable, the univariate type is applied. Therefore, the variogram in this case can be written as a linear combination of its components. In this research, the gravity data, acquired from Faryab chromite mine area, are processed and interpreted using the FKA method. Based on this study, three components, which may represent regional, local, and noise components are defined and filtered based on spatial structure study. Moreover, two locations are proposed for further detailed exploration considering the extracted local component map. Also, the gravity data are processed using potential field filters. In this regard, different heights are considered in the upward continuation filter method applying on the gravity data, and then, the results are shown in the relevant maps. Low value gravity anomalies can be interpreted as the geological structures having low density or special geometric shapes such as a geo-anticline. High value gravity anomalies can be considered as densie masses like chromite lenses. Finally, in this research work, the obtained results from applying the FKA method on the gravity data are compared with the potential field filtering results using the upward continuation filter method. The basic difference between the upward continuation and the FKA methods is that the latter method takes into account the spatial structure of the data while the former does not. This study clearly indicates the capability of the FKA method in filtering gravity data.

The gravity method is one of the first geophysical techniques used in oil and gas exploration. An algorithm is developed for a fast quantitative interpretation of gravity data generated by geometrically simple but also the estimated depths and other model parameters of a buried structure. Following Abdelrahman et al (1989). The general gravity anomaly expression produced by a sphere, an infinite long horizontal cylinder and a semi- infinite vertical cylinder can be represented by the following equation (1) where and z is the depth of the body, xi is the horizontal position coordinate, σ is the density contrast, G is the universal gravitational constant and R is the radius and q is factor related to the shape of the buried structure and is equal to 0.5,1.0,and 1.5 for the semi- infinite vertical cylinder, horizontal cylinder and the sphere respectively. Consider nine observation point (xi -4s), (xi -3s), (xi -2s), (xi -s), (xi), (xi +s), (xi +2s), (xi +3s), (xi + 4s), along the anomaly profile where s=1,2,3,M spacing units and is called the window length. Using equation (1) the simplest first numerical horizontal gravity gradient (dg/dx) (2) the second horizontal derivative gravity anomaly is obtainedfrom equation (2) as (3) the third horizontal gradient is(3) (4) Similarly, the fourth horizontal gradient is (4) 5) Which yields; Where (7) Equation (5) can also be solved using a simple iteration method. Equations (5) can be used to determine the depth and the shape of a buried structure using the window curves method. The validity of the method is tested on synthetic data white and without random errors. The method was applied to a gravity anomaly from the Abade of Iran. The results shows that the s-curves intersect each other in a narrow region where 7.220 Keywords: Gravity anomalies, Depth, shape estimation, Numerical fourth horizontal derivative, The s, curves method