مجله ژئوفیزیک ایران
سال یازدهم شماره 5 (پیاپی 37، Winter 2017)

The time for easy oil discovery and production for National Iranian Oil Company (NIOC) is over. This means that the oil is no longer discovered in structurally simple, i.e., almost flat environments like south of Khuzestan province (south west of Iran). This comes along with the fact that Iran’s biggest oil reservoirs are in this area, and they are passing half of their life cycle. These giant reservoirs are still producing more than half of oil production in Iran. There is significant uncertainty in future of Iran oil and gas exploration. In fact, the rate of drilling a successful well by NIOC exploration directorate is dramatically reduced in past few decades. The reason is that nowadays NIOC is drilling in structurally complex areas such as Zagros thrust belt mountains with rough topography and complex geology. Uncertainty in the drilling arises mainly from many factors, one of which is the processing tools in NIOC repository that belongs to at least 30 years ago. These tools belong to the time when NIOC used to drill for easy oil. In addition to the processing, other parts such as exploration techniques need to be revised in structurally complex environments. This article briefly looks at processing tools, which are critical to be used by NIOC to be able to significantly improve the drilling success rate.

Surface nuclear magnetic resonance (surface-NMR) method is a well-known tool for determining the water-bearing layers and subsurface resistivity structure. Harmonic interference is an inevitable interference in surface-NMR measurements. Accurate estimation of harmonic interference parameters (i.e., fundamental frequency, phase and amplitude) leads to better retrieval of power-line harmonics and consequently, more effective suppression of harmonics from surface-NMR recordings. To that end, two algorithms are addressed for isolation and then subtraction of harmonic interfering noise based on modeling of power-line harmonics by a modified version of Nyman-Gaiser estimation (NGE) and residual signal power (RSP) technique. Then, the results derived from the proposed algorithms are analyzed and compared through the modeling of some synthetic signals embedded in simulated noise and real recordings obtained from multi-channel surface-NMR measurements. The numerical experiments on simulated and real surface-NMR signals show that the application of the proposed procedures results in significant decline of the level of the standard deviation of imaginary part of the detected signal and consequently, relatively accurate recovery of the harmonic signal components with an accompanying enhancement in estimation of the surface-NMR signal parameters.

In the current work, a 2D non-linear inverse problem of gravity data is solved using the evolution strategies (ES) to find the thickness of a sedimentary layer in a deep-water situation where a thick sedimentary layer usually exists. Such problems are widely encountered in the early stages of petroleum explorations where potential field data are used to find an initial estimate of the basin geometry. However, the gravity data are the non-unique problem, and classical deterministic inversions can only offer a single approximation of the solution. Conversely, ES and evolutionary algorithms in general due to their random nature can offer a range of solutions that all fit the data within the acceptable threshold. The inverse problem is formulated as a single objective unconstrained numerical optimization. In evolutionary algorithms, the random nature of the search follows the same rules of the Darwinian biological evolution. Hence, the search is not exhaustive and requires less computational resources compared to Monte Carlo methods. Herein, first, the algorithm is introduced, and a classical synthetic problem is formed and successfully solved in the presence of white Gaussian noise. Then, a two-layered synthetic oceanic crust is formed. ES is successfully tested for solving the formulated under-determined inverse problem of estimating both the base of the sedimentary layer and the crust (i.e., Moho boundary). Finally, using the proposed method, the thickness of the sedimentary layer of the Caspian basin is found along an E-W profile crossing the Caspian Sea. The results have a good agreement with the previous estimates by deep seismic sounding method. The proposed method could be of particular interest because, in deep-water situations, the high water content of sediments, and the expected large thickness of the sediments among other factors make the use of reflective seismic methods unfeasible.

Space-borne gravity data from Gravity Recovery and Climate Experiment (GRACE), as well as some other in situ and remotely sensed satellite data have been used to determine water storage changes in Lake Urmia Basin (Iran). As usual, the GRACE products are derived from precise inter-satellite range rate measurements converted to different formats such as spherical harmonic coefficients and equivalent water thicknesses of juxtaposed tiles in which the corresponding mass anomalies are estimated, resulting in missing information during these time-consuming processes. In this paper, GRACE level 1B K-band range rates related to Urmia Basin are corrected for non-hydrological processes and the resulting time series are analyzed using wavelet transformation. On the one hand, direct corrected range rates are employed to make an unevenly spaced time series. In addition, the monthly mean measurements of the same type are applied to create uniform time series. Therefore, a wavelet-based least-squares spectral analysis method is introduced to extract the general behavior of irregularly sampled time series. In addition, the classical wavelet transformation is used to analyze the monthly averaged time series. The results indicate that the extracted coarse parts of the corrected range rates have significantly changed between 2007 and 2008, which are in good agreement with the total water storage (TWS) changes modeled in Urmia Basin, as well as with the similar previous research findings. Besides, the time-frequency behavior of both TWS changes and monthly averaged range rate time series show that the extracted annual constituents, as the main parts of the signals, have mainly weakened after 2007.GRACE, least squares approximation, time series analysis, wavelet transform, Urmia Basin

On August 7, 2003 the Cluster spacecraft moved through the dayside magnetosphere. The energetic particle spectrometer on board Cluster provided measurements of an extensive range of energy. Besides, satellite measurements of geomagnetic field showed a gradient magnetic field. It is known that an inhomogeneity of the magnetic field leads to a drift of charged particles. In this paper, the drift velocities including gradient drift and curvature drift have been calculated for an energy range from 0.1 to 300 keV via various pitch angles (about 6 to 9 UT). The pitch angles in the magnetic equator via the magnetic mirror location have been calculated near the magnetopause. Besides, the ratio of perpendicular particle energy over total particle energy as a function of equatorial pitch angle has been calculated. The drift velocities depending on the pitch angle for the low energy (0.1 kev) is about 0.01-0.07 km/s and for the higher energies of the particles (300 kev) is about 50-200 km/s between L ≈ 4 to L ≈ 6. The results show that particles with higher energies penetrate the deeper areas of the magnetosphere.

Unconventional resources are typically very complex to model, and the production from this type of reservoirs is influenced by such complexity in their microstructure. This microstructure complexity is normally reflected in their geophysical response, and makes them more difficult to interpret. Rock physics play an important role to resolve such complexity by integrating different subsurface disciplines. This study presents two rock physics workflows for a deeper understanding of shale reservoirs with regard to their matrix brittleness and kerogen content maturity. It first employs petrophysical stochastic modelling on the available conventional well logs. Then, the results of well log interpretation are used as input into a rock physics model to generate a complete set of elastic logs. Furthermore, these elastics logs are converted to Young modulus and Poisson’s ratio for highlighting brittle zones, which were confirmed by production figures. Moreover, another rock physics workflow is proposed to combine geological information and petrophysical data to characterize total organic carbon content of the shale. This rock physics model inverts velocity into its main geological components (organics, clay and clean velocities), which could furthermore be used for velocity interpretation considering geological processes. One of the velocity inverted components has a direct relationship with total organic carbon and its maturity that is normally calculated using Passey method. Passey method uses three different well logs for modelling kerogen maturity along a well path. However, implementation of this model at locations far away from the well is a big challenge for field development. The reason is the difficulty of tying Passey method results with the elastic properties and seismic cubes. The proposed geology guided rock physics model enables us to find a relationship between kerogen maturity and P-wave velocity from sonic logs. This model, furthermore, can provide a tool to somehow extend Passey method into seismic cubes.