IRANIAN JOURNAL OF GEOPHYSICS
Year:2012 | Volume:6 | Issue:2|Papers Count:10

In this study after considering the importance of the stress filed and its applications in different branches of earth sciences, the focal mechanism stress inversion techniques were reviewed in a short way. Although the problem in hand was highly nonlinear, according to the benefits of the linear approaches some authors have tried to linearize the problem by making some extra assumptions in addition to the assumptions that all stress inversion methods share i.e. homogeneity of the stress tensor in the area or assuming the slip direction to be in the direction of maximum shear traction. Therefore two different approaches, linear and nonlinear methods were investigated in this study.Then two major methods from each division namely Michael (1984) from linear approaches and Lund and Slunga (1999) from the nonlinear ones, were selected and the main aspects of each method were shortly described without entering into details. After that each method was applied to a dataset from a previously studied and widely known area in California, United States of America, to ensure the validity of the results. The results from both methods showed good agreements with the expected results based on the successful studies in the area about the stress field performed by Angelier (1979).Some of the differences observed in the results from different methods are due to the way they make choice between the nodal plains. In Michael (1984) method this choice is being made during the bootstrap randomly, thus there is a similar chance for each nodal plane to be selected as a fault plane. This increases the ability of the method to deal with the noisy data. On the other hand Lund and Slunga (1999) method has the ability to select the fault plane based on two different methods which are slip angle and instability. The experience of using these methods shows that the Michael (1984) method generally gives an average orientation of the maximum horizontal stress that approximately occurs between the two methods introduced by Lund and Slunga (1999).Finally the methods were applied on a dataset from Makran region which is placed both in Iran and Pakistan. The result of the stress inversion of all available data from Makran was an average of the SHmax (maximum horizontal stress) directions in the area and therefore the dataset was divided into three different parts: western, central and eastern. The result showed an interesting variation in the maximum horizontal stress directions. Different methods used in this study showed a good agreement again and this led to the higher reliability of the stress directions in Makran.These directions showed a variation which was acceptable according to the tectonic state of the region and also the previous studies in the region. In the western part of Makran, the maximum horizontal stress orientation was 17.6±4, parallel to Zagros, and showed the effect of the continent-continent collision between Arabia and Eurasia plates. In Central Makran, this direction showed a clockwise rotation and became 38.2±3. In the eastern part which is under the influence of the continent- continent collision between Indian and Eurasian plates, the direction was 157.0±4. Paying attention to these variations in stress states can be helpful to study the area especially in the western part of the Makran subduction zone which is associated with lack of seismicity. The observed correlation of the variation in crustal stress and the seismicity agrees with the recent studies reporting a similar correlation between the seismicity and the upper mantle velocity variations obtained from surface wave tomography. It confirms the changing nature of the subducting slab stretched from west to east in Makran subduction Zone.

The energy released from an explosion propagates through the surrounding rock-mass in wave forms, causing structural vibrations in the vicinity of the explosion blocks. The waves are spread as body as well as surface waves. Resonance occurs when the frequency of the explosion wave is the same as the associated structures, leading to increase the damage to them. Hence, in designing the explosion patterns, the allowable peak particle velocity of these structures should be considered. Several correlations (Pears, 1955; Allsman, 1960; Speath, 1960) presented in the literature, express the parameters involved in evaluating the explosion effects including the explosive characteristics and the rock-mass strength. Ash (1968), proposed a simple relation based on the diameter of blast-hole to determine the burden required and Livingston (1956) suggested a relation on the basis of “crater theory” to determine the spacing. However, the influence of blast-wave has not been considered in the conventional explosion design patterns. In this study, a neural network was trained in order to design a explosion pattern based on the maximum allowable vibration. This network tried to design a blasting pattern by special attention to the allowable peak particle velocity and the natural frequencies of the buildings adjacent to blasting area. For this purpose, the ground vibration data from 11 blasts were recorded by PDAS-100 digital seismographs and 3-C L-4C seismometers. Seismographs were installed in three vertical, tangential and radial directions. 47 of the recorded vibrations were employed in a neural network training which used a back propagation algorithm for training. The network consisted of four hidden layers and one output layer composed of three neurons. The training algorithm of each hidden layer was a Levenberg-Marquardt designed to approach a second-order training speed without having to compute the Hessian matrix; Tan-sigmoid transfer function was employed for the hidden layers and a linear transfer function pureline was used for the output layer. For adequate network training process, a series of appropriate response should be ensued. During the training, in order to minimize the performance, the network weights and biases were corrected. In this study the network performance was evaluated using a mean-square error when compared to the output and the real data. The input parameters included the peak particle velocity, frequency, volume of the extraction block and the explosive density, while the outputs included the burden, spacing and the total charge weight. The other parameters of the blasting pattern such as stemming, sub-drilling were calculated by empirical equations and the blasting delay was determine by the blasting designer. The network was trained successfully at the 8920th epoch with a mean square error of 6.19´10−16. To ensure correct training, the network was tested using the test data and was able to achieve the total charge weight, burden and spacing with coefficient correlations of 0.65, 0.77 and 0.96, respectively.

Since the beginning of seismology, a hundred years ago, seismologists have always been hopeful to be able to predict earthquakes in order to help populations across the globe avoid destruction and casualties. However, earthquakes continue to occur without any warning. Soil and groundwater gas variations due to the change in stress related to seismotectonic activity are well documented and used extensively in seismotectonic studies, including fault tracing and seismic surveillance as a precursor. Radon has a more sensitivity than other precursory gases and is considered as the most appropriate gas form precursor.The first continuous radon monitoring station in Iran, for assessment of radon as an earthquake precursor, was established in September 2007, in Jowshan hotspring (N 30o09' 38.7" – E 57o35' 57.5"), Kerman Province, SE of Iran. Jowshan complex is composed of six springs, which outflow through fractured limestone, along the Gowk fault. This fault is stretched from the southwest of Bam Plain to the west of Shahdad Town which is well-known for its reservoir-triggered seismicity and has an active history. Occurrence of more than 20 earthquakes M>5 in the 20th century (According to IIEES earthquake catalogue). As an example, Bam earthquake with M 6.6 (According to USGS data) and more than 25000 victims on December 26, 2003, represents this active history. In this study, in order to measure radon concentration in the spring water, an Alpha Guard PQ 2000 PRO (Genitron Instruments) detector was used. This instrument with a resolution of 1 Bq/m3 is able to measure 222Rn concentration from 2 to 2000000 Bq/m3. Detection of Alpha (a) particles produced by radon decaying in the ionization chamber depends on the instrument. This detector, like the most of the radon detectors, has measured the concentration of radon in the gas phase - not in the liquid phase. Therefore, at the beginning, the radon must be transformed from liquid phase to gas phase. The detector was setup in the Jowshan hotspring outlet as shown in Figure 1, schematically. In this system, water enters into an exchange unit which acts as a flow stabilizer. Gaseous radon that leaves the spring water by diffusion is pumped into the detector. This instrument has humid sensitivity. Therefore, the air contains radon cross from humidity absorption chamber (Silica Gel). In this study, a sodium chloride crystal was used as a humidity absorber. Radon was detected every 10 minutes by mentioned instrument and the results were saved into the internal memory of detector.There are different experimental equations concerning the relation between earthquake magnitude and its effective range on geo-gas variations. According to Dobrovolsky’s empirical relation (D=100.43M) and the stress-strain theory, strain distribution radii (D), depend on the earthquake magnitude (ML). Therefore, anomalies due to earthquakes can indicate whether precursor monitoring station lies in the stress-strain field. Three spike like radon anomalies have been observed several days prior the M 4.9 Shahdad and M 4.3 Sirch earthquakes that occurred on May 11 and 12, 2009, respectively. Location of Jowshan hot spring in the stress-strain field of 11/05/2009 and 12/05/2009 earthquakes in Shahdad and Sirch respectively, can be ascribed to the radon concentration anomalies on 05/05/ 2009 and 09/05/2009.

Conventional methods of velocity analysis are equivalent to modeling prestack seismic data with events that have a hyperbolic moveout. Examples are included which demonstrate the depth, overlapping events and the details of the closed layers.Various types of measured coherency that can be used as attributes in computing velocity spectra are described here and some of them which are discussed in this paper are: Stacked amplitude (S), Normalized stacked amplitude (NS), Unnormalized cross-correlation (CC), Energy-normalized cross-correlation (EC), Semblance (NE) and AB Semblance. It is should be noted that all these methods are based on the correlation between the traces. The equations of different methods are described and coded based on the corresponding literature and then applied to synthetic data. The results of these methods are compared in velocity and time with each other and their accuracy are examined. Four factors are introduced to compare the results of the velocity analysis methods. The first factor is the contrast which means the ratio of the coherency in the exact velocity to the coherency of the near velocities. The second factor is the smearing on data that measures the accuracy of the method used in detecting the velocity and the time of the events; it equals to the smearing in half of the difference between the coherency of the pick and the average coherency of the background. The third factor is the ability of the velocity distinction, it means how much a method can make difference between two near velocities. And the last factor is the ability of time distinction which indicates how much a velocity analysis method is able to detect two near layers with higher resolution. Fitness plots compare the performances of the six methods when the velocity analysis is done on the same events in both time and velocity aspects. The sharpness of the fitness curves is in the relation with the velocity and time resolution. Then we introduced more noise to data and discussed the effect of noise on the quality of the velocity analysis. Also the effect of the noise contamination is clearly explained and can be seen in another fitness plot. Additionally synthetic data contains various multiples and overlapping events with different changes. Finally, CC, Semblance, and AB Semblance led to the best results, however; the AB Semblance proves its accuracy by maximizing a coherent measure in correct velocities and times and also by minimizing a coherent measure in incorrect velocities and times. Compared to the AB Semblance the vulnerability of the other methods to the coherent noise is better understood.In the next step, these methods were applied to real data belonging to one of the southern oil fields in Iran and again the AB Semblance led to the best results. This method, in contrast to others, does not stretch velocities and displays shallow events as clear as deep events. We concluded that the AB Semblance method is able calculate the velocity and distinguish between the closed layers clearly better than the other methods.

Drilling and blasting have numerous applications in civil and mining engineering. However, there are many unfavorable associated side effects and hazards, such as ground vibrations, air blasts, fly rocks, back-breaks, unwanted displacements, crack formation and propagation, and extended crushed zones, all of which need to be predicted and controlled effectively. Ground vibrations caused by blasting can damage the zones in the vicinity of the explosion block and its associated civilian structures and equipment. In addition to environmental and structural damages, air blasts can irreversibly damage the health by affecting the hearing sense and mental stability of the personnel. Damages to the front face, caused by open-pit and underground explosions, not only increase the maintenance costs, but also make the appearance unacceptable. An important factor in reducing hazards in controlled blasting is the prediction of crack formation around the blast-hole and its propagation, which has been the subject of research since early 1950’s using field experiments, analytical methods and numerical simulations, paving way for many semi empirical correlations presented in the literature on this matter. As a rule of thumb, the radius of the crushed zone and the length of the radial cracks, are assumed to be in the order of 3 to 5 times and 40 to 50 times that of explosive radius, respectively. Hence, the radius of the crushed zone and the radial crack lengths were evaluated to be 10.16 cm and 114 cm, respectively. In this study, the results of the field studies from single blast-holes in the mudstones of Gotvand Olya dam were compared with several empirical correlations, using a blast-hole of 76 mm diameter, 2 m depth, 1 kg emulate 27 charge and a single instantaneous electrical cap. Two seismometers of VIBROLOC placed 8 m and 13 m away from the blast-hole recorded the ground vibration at 17.22 and 9.02 mms-1, respectively. The crushed zone radius and the radial crack length were measured to be 25 cm and 90 cm, respectively. The crack propagation and the ground vibration were compared with the field study results using a UDEC discrete element method. In the simulation exercise, the dynamic loading on the surrounding walls of the blast hole were assumed to be uniform and in radial direction. Also, the blast was assumed to take place instantaneously along the cylindrical charge and the semi-empirical relationship of Liu and Tidman was used to evaluate the maximum detonation pressure produced. The simulation results included a variation in the peak particle velocity with respect to the distance from the blast hole centre, a variation in the particle displacement, a variation in the applied stresses caused by the shock wave travelling, reflecting the stress wave from a free face. The numerical analysis indicated the crushed zone radius and the radial crack length to be 20 and 90 cm, respectively. Also, the ground vibrations at 8 m and 13 m distances away from the blast-hole were simulated to be 17.2 mms-1 and 9.27 mms-1, respectively. Amongst the empirical correlations used, Ash correlation (1963) revealed a radial crack length of 110 cm, and Essen et al. (2003) evaluated a crushed zone radius of 19 cm, indicating more accurate estimations. This study indicates that the numerical analysis used is capable of presenting acceptable accuracy.

Earthquake process involves different variables some of which are determined more accurately than the others with non-modeling approaches. The scope of this research is to investigate the effect of individual geometrical and physical input parameters in coseismic gravity change models on the Earth surface. Among different physical and geometrical parameters, performing sensitivity analysis on less accurately determined parameters by field work is recommended. Among these parameters we can refer to fault dip and upper locking depth of the fault. Nevertheless in this research the role of all faulting parameters on gravity obtained data have been surveyed. To do this analysis the elastic model of Okubo (1992) was used. In this research, surface gravity change was modeled in three strike-slip, dip-slip and tensile slip reference faults, in a medium composed of an elastic half-space and a sensitivity analysis was performed on all geometrical and physical parameters. From the variability analysis, the location of the most appropriate gravity data was determined to obtain values for the studied parameters. To do sensitivity analysis, we considered areas with maximum and minimum gravity changes. These areas were located on one end of the surface projection of the reference fault plane in a strike slip case and middle of the surface projection of fault plane in dip slip and tensile slip cases. In all cases the characteristic horizontal length scales were fault dimensions. Maximum and minimum gravity changes were principally by the magnitude of slip or dislocation. On the other hand, fault size has a much smaller effect upon them. According to results obtained from the analysis, coseismic gravity changes showed a high dependency to fault slip above rupture surface of the fault; however it showed the least sensitivity to the fault length as well. Therefore, this model was not an appropriate tool to determine the fault length. Analyzing the coseismic gravity changes revealed a strong dependency on the dip angle of the fault plane. Observation points with large gravity changes also showed a large variability as the dip angle of fault varied. The area over the rupture plane was the one where the largest gravity changes occured. Therefore, surface measurements in this area were the most suitable to ascertain the most likely value for the dip angle. In the analysis of the coseismic gravity changes it was found that, on average, deviations from a reference model were large above the rupture plane when varying the upper locking depth of the fault. on the other hand, varying the elastic half-space density led to small differences, in general. It means that coseismic gravity change analysis shows a small sensitivity to the elastic half-space density. This, in turn, indicates that coseismic gravity measurements are not recommendable for trying to ascertain an accurate value for this parameter. This model does not show any sensitivity to Lame coefficients for Poisson Solid. Earthquake parameter determination specially dip angle and upper locking depth using Multi-purpose Physical Geodesy and Geodynamics Network of Iran (MPGGVI) was an important applicable result of this research. Densifying of this network in seismic zones of Iran is recommended for better inverse problem solution using these network observations.Sensitivity analysis of Soldati (1998) model for viscoelastic half-space is recommended. The results of this analysis could be used for fault parameters determination by gravity network set up in postseismic mode.

Nowadays, geophysics, and three-dimensional (3D) ground geoelectrical methods in particular are successfully associated with environmental investigations. The waste produced by coal washing operations often contains sulfide materials specifically pyrite.The appropriate atmospheric conditions and moisture favor rapid pyrite oxidation and subsequent acid mine drainage (AMD) formation. This AMD that contains high concentrations of iron, sulfate, low pH and variable concentrations of toxic metals is a major cause of long-term environmental problems.Since, the pollutants produced by pyrite oxidation processes in the groundwater flow system may change considerably the conductivity of the polluted zone, the electric and electromagnetic (EM) geophysical methods could effectively be used to map these zones. Resistivity and very low frequency electromagnetic (VLF-EM) are commonly used for this purpose.This paper discusses the results of a geophysical survey incorporating two different methods comprising VLF-EM and 3D electrical resistivity and attempts to detect the pollution emanated from the wastes produced by Alborz Sharghi Coal Washing Plant. This plant, which is located at 380 km northeast of Tehran and 57 km northwest of Shahrood City in Semnan Province, has being working for 30 years. The input feed of the processing plant is 500, 000 ton per year. The coal recovery in the plant is 50%. The rest of the input feed is dumped as wastes around the plant. Depending on the method used for coal processing, two kinds of the waste are produced and dumped in the distinct places. The first kind is produced by a jig machine while the second is produced by a flotation process. It is expected that the amount of the coal waste to be about 3 million tons in the study area.A geophysical survey using the VLF-EM method was first performed with a measuring spacing of 5 meters on 4 parallel profiles of 30-m distance in the downstream of the waste dump in order to investigate the likely polluted zones. The VLF measurements were carried out using a portable WADI-VLF digital instrument of ABEM Co. The measured data was then processed using RAMAG computer software. To simplify the data interpretation, the VLF raw data were filtered using the Karous-Hjelt technique and a set of vertical current density pseudo-sections were provided. The results of interpretation detected two polluted zones in the downstream of the waste dump. These polluted zones can be easily recognized between profiles 1 and 3 with high values of current density. The VLF survey was found to be good in identifying the path ways for pollution movement downstream the coal washing dump, but limited in its ability to exactly distinguish the depth of polluted zones. Due to this problem, the area located between profiles 1 and 3 was then selected for a 3D geoelectrical survey to better investigate the pollutant leaching process. The electrical resistivity method produces an image and/or an approximate model of the subsurface resistivity. Various arrays including pole-pole, pole-dipole, and dipole-dipole arrays are normally used for 3D resistivity surveys. In the present research, a 3D geoelectrical survey using a pole-dipole array was carried out on a 6´6 rectangular grid with different electrode spacing of 15 m and 30 m in x- and y directions, respectively by a portable SAS 1000 instrument from ABEM Co.As the pole-dipole array is an asymmetrical array, measurements were made with the forward and reverse arrangements of the electrodes on each profile in x- and y directions. Two more profiles were also considered in the direction of diameters of the rectangular grid.A computer software called RES3DINV which incorporates a smoothness-constrained least-squares approach was then used to perform an inverse modeling on the measured apparent resistivity data. To perform a 3D inverse modeling, the subsurface of the survey area was divided into several layers and each layer was further subdivided into a number of rectangular blocks with unknown resistivities. The interior blocks within each layer had the same size. The main objective of the inversion process was to determine the resistivity of each block in a manner that the model response fitted well the measured apparent resistivity data. The RES3DINV program utilizes least squares Gauss–Newton and quasi-Newton optimization methods for modeling process. This model can apply both numerical finite difference (FD) and finite element (FE) methods for calculation purposes.The results of inversion have been provided as sets of horizontal and vertical resistivity sections and also a 3D resistivity model was finally presented using Slicer\Dicer software. This 3D geoelectrical model illustrated a polluted zone with a thickness of about 30 meters at the depths between 30 and 60 meters.

Determination of porosity distribution is important in hydrocarbon reserve estimation, facies variations, optimized planning for field development and decrease in drilling risks and costs. Porosity is one of the most important parameters, which is considered as a fundamental factor in reservoir engineering. By knowing this parameter, specialists are able to design and manage, effectively, the process of oil and gas field development. Seismic attributes and well logs are the data available in most of the reservoir studies. Seismic attribute analysis is generally done through correlating multi attributes to the reservoir characteristics. A good interpreter needs to observe several maps with certain information to prepare optimal drilling points. Such a process is long and exhausting with high probability of error. We present in this paper a method to ease the interpreter’s task of analyzing dozens of seismic attributes by integrating all the information into just one map, this map, the similarity map, shows the resemblance of the seismic response of each region of the whole study area with respect to a selected location in the field. In this paper, 3D seismic data in the study area are interpreted using well data. In addition, seismic inversion was conducted in order to estimate the porosity distribution based on the acoustic impedance within the study area. Moreover, an attempt was made to predict the effective porosity by designing a probabilistic neural network (PNN) and simultaneously using seismic attributes and effective porosity logs in the reservoir window. This was done by deriving a multi-attribute transformation between an optimum subset of seismic attributes and effective porosity logs. Seismic traces close to the well locations were used to generate seismic attributes. Effective porosity logs at the reservoir area were the target logs in this study. A set of seismic attributes were generated using HRS software and a forward stepwise regression process was used to determine an optimum subset of attributes to be utilized in the training of neural networks. Ultimately, we obtained a porosity map of the studied area. The inputs of the similarity analysis included a set of uncorrelated seismic attribute maps, the coordinates of the control point, and the radius around the control point that circles an area (the reference zone) of nearly constant attribute response. Four different attribute volumes generated were then used in the study: instantaneous amplitude, instantaneous phase, instantaneous frequency, and acoustic impedance. A horizon-slice at the reservoir was extracted from each of the attribute volumes. First, Well 08-08 (a high producing well) was chosen as a reference well. The selection of the reference well could be the highest production well, the lowest production well, a dry well, or any other classification depending on the objective of the analysis. The objective was to map the reservoir of the field based on the reference point 08-08 for possible high production areas. A radius value around the well was then chosen to calculate the mean and the standard deviation of the reference point within the radius from the extracted horizon slice for each of the attributes. The output of the first step was (N) different reference means and reference standard deviation for the same reference point; (N=4) is the number of attributes that were used in the study. The next step was to calculate a zero-one matrix from the extracted horizon-slice for each attribute based on a statistical criterion that would assign either zero or one to every node for a given horizon-slice. Finally, zero-one maps were integrated into one single map. The four attributes revealed different information and their zero-one maps showed different distributions that help the interpreters correlate each map to other types of information such as production or geologic information. The final map was obtained by integrating the zero-one maps. Studying the results obtained from the “similarity map” and “porosity map” in reservoir zone presented a convincing correlation between the two maps found through different methods each having specific information for the interpreters and helping them make more reliable decision to choose a prospective point, with less drilling risks.

A useful method to increase the signal/noise ratio of refracted waves is Common-Midpoint Refraction (CMPR) seismics. Consider a plane wave traveling from the source location A to a receiver point B (or vice versa). The distance between the two locations A and B is denoted as x. If the reference point Xr is the is the CMP between A and B the relation xA=xB=x ¤ 2 is valid and one can write its travel time equation based on the ray parameters and vertical slowness (Diebold and Stoffa, 1981). For such a model, Slotnick (1936) obtained an equation which is the basic equation for depth conversion in CMPR method.With this technique, the shallow underground can be described in detail using all information (amplitude, frequency, phase characteristics) of the wavetrain following the first break (first-break phase). Thus, the layering can be determined and faults, weak zones, and clefts can be identified. This will be done by stacking a trace in a t-p domain. Since the stacking data along the straight line of the Radon transformation is used to suppress reflected wave groups and surface waves in CMPR method, the Radon transformation must be restricted to refracted waves only. After Radon transformation, an intercept-time section is made.The following difficulties occur when dealing with CMPR seismics.1. The data will be sorted as CMP-offset gathers. Therefore, the distance between two traces is twice the distance between two shot points. Thus, optimum stacking velocities for the partial Radon transformation in CMPR seismics cannot be determined.2. Local variations in refractor velocities are difficult to record.3. In routine CMPR seismics, the traveltime branch of the total refracted signal is stacked. Therefore, local irregularities of interest cannot be detected.These disadvantages are rectified using a combination of CMPR seismics with the Generalized Reciprocal Method (GRM; Palmer, 1986). This joint application is possible because of the close relationship between both methods in their kinematical descriptions.Gebrande (1986) described a technique to construct CMP traveltime curves using the data from only one forward and one reverse shot. Using this technique, the CMP intercept time would be in the form of an equation which have some similarities in comparison to in GRM. These similarities and their relationships are helpful in rectifying certain disadvantages in the CMPR method. TG Velocities and optimum offsets determined by the GRM can be used directly in the partial Radon transformation in CMPR. The result of this process is an intercept-time section which can be converted directly to a depth section.In the partial Radon transformation of joint CMPR seismics with the GRM, the stacked events are only those that belong to the critical offset in the CMP-offset gather. These events are principally the critical reflected waves. Therefore, the migration of the intercept-time section must employ a post-stack method such as Kirchhoff migration. After migrating time section it can be converted to depth section using its individual equation.Using two models for numerical investigation, the efficiency of the method is tested, and the results are shown.

Divergence and vorticity are two most attractive and popular quantities in the study of sever atmospheric phenomena. On the other side, the role of deformation, especially total deformation–expect for a few cases related to the frontogenesis theory–has received less attention of scientists. This study is trying to fill this gap a little. It is trying to examine the role of deformation in general and the stretching deformation, shearing deformation and total deformation in particular on precipitation. In doing so, the GFS (the Global Forecast System) wind components data in five years (2003-2005) were used to compute the stretching deformation, shearing deformation and total deformation in a network covering the Iranian and influential surrounding area.In order to evaluate the effect of the deformation field on the atmospheric variable here we used the collective 24 hours precipitation reported by the synoptic observatory around the concerned domain. Due to the irregularity of the observatories in the beginning, the reported data of the rainfall from synoptic stations were moved to regular grid points applying Cressman objective analysis method. The distribution maps of precipitation and contours of stretching deformation, shearing deformation and total deformation also were prepared.Comparison of the precipitation maps and the maps of stretching deformation, shearing deformation and total deformation in six, twelve and eighteen hours before the occurrence of precipitation, showed that in the concerned region the flux of total deformation pattern (dot product of the total deformation and the wind) was more consistent with the precipitation maps in 6 hours later. Therefore, the flux of the total deformation has a predictive value for precipitation and could be used as a precursor of precipitation. Besides the general matching of the patterns of the total deformation flux and precipitation, the location of the maximum precipitation occurrence is reasonably compatible with the location of maximum flux of total deformation in six hours earlier. In the grid points of significant values of the precipitation, the total deformation fluxes were calculated for comparison. Also for more precise investigation, the values of the cumulative rainfall were divided into three groups (0-10), (10-20), (20-30) mm and the values of the total deformation flux were computed for each of these intervals. It has been verified that the interval of 0-10 has the maximum frequency of happening regardless of value of deformation flux magnitude. The probability that precipitation occurs between 0-10 is 26%. Also the probability of occurrence of larger deformation flux decreases exponentially as the value of deformation flux increases regardless of value of precipitation.The results of the computation show that the total deformation flux is varying between 5e-5 and 10e-5 for all intervals of the three groups of rainfall. The elongation of the dilatation axis of the total deformation for all available data was computed. Based on the results of this computation the axis of dilatation in severe rain falls are elongated in the direction of West-East, Southwest-Northeast and North–South depending on the raining area and the core of maximum precipitation.