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SUMMARY In this paper we propose an approach to improve the efficiency of the regularized Gauss-Newton inversion algorithm by using an adaptive cross approximation (ACA) technique. We apply the ACA technique to decompose the Jacobian matrix into two smaller rectangular matrices. In this way we improve the efficiency of the Gauss-Newton method on both memory requirements and CPU time. The improvement increases when we deal with large data sets with a large number of transmitters, receivers and frequencies. To demonstrate the improvements introduced by this method we present results of both synthetic and field data inversions for controlled source electromagnetic surveys. INTRODUCTION The marine controlled-source electromagnetic (CSEM) technology has the potential of providing useful information in applications such as off-shore oil exploration. With a horizontal electric dipole as a transmitter towed by a ship and multicomponent electromagnetic receivers placed on the seafloor, this method has been applied in several field surveys. The high contrast in resistivity between saline-filled rocks and hydrocarbons, makes this method well-suited for detecting resistive hydrocarbon reservoirs (see Constable et al. (1986); MacGregor and Sinha (2000); Ellingsrud et al. (2002)). The approach initially employed is based on comparing the electric field amplitude as a function of the transmitter-receiver offset with a similar measurement for a non-hydrocarbon bearing reservoir, see Srnka (1986); Chave et al. (1991); Sinha (1999). The presence of hydrocarbon raises the amplitude of the measured electric field indicating the existence and, to some degree, determining the horizontal location of the hydrocarbon zone. However, with this approach it is difficult to know the reservoir’s depth and shape. A more rigorous approach to address this type of application is the full nonlinear inversion approach, for example see Abubakar et al. (2006), Gribenko and Zhdanov (2007), Plessix and van der Sman (2007) and Abubakar et al. (2008b). In such an approach the investigation domain is subdivided into pixels and by using an optimization process, the location, the shape and the conductivity of the reservoir are reconstructed. Most of these methods use iterative schemes, in which the conductivity distribution is updated based on a search direction computed from a gradient of a cost function. Therefore, in these derivative-based approaches the Jacobian matrix plays a key role. This matrix contains information about the derivative of the simulated data with respect to the conductivities of the unknown pixels. Its size is equal to the number of measurement data times the number of unknown pixels. In the CSEM data inversion, the size of the data set and the inversion region can be very large. Hence, the storage of the Jacobian matrix requires a huge amount of memory. This is one of the bottlenecks of using the nonlinear inversion approaches. Moreover, because the Jacobian matrix is a dense matrix, the arithmetic operations of a matrix-vector multiplication can be very expensive as the size of the Jacobian matrix increases. Currently, in order to be able to process the data, we usually invert only a subset of the data. However, the choice of this subset is often based on the experience of the data interpreters.
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Sognefjord Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Heather Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Fensfjord Formation (0.99)
- (9 more...)
Summary The seismic physical modeling facility at the University of Calgary has existed since 1985. Recently, we upgraded it by replacing obsolete components with modern alternatives. We constructed a 3D positioning system based on high-precision linear electric motors, and coupled it to arrays of multiple transmitting and receiving piezoelectric transducers. We wrote customized software executing on the latest generation of desktop computers for controlling transducer movements, selecting and activating individual transducers, and acquiring and recording files of digital seismograms. The modernized facility enables us to collect scale-model seismic gathers at rates of thousands of traces per hour. We present examples of data from modeled 2D marine and land seismic surveys. Introduction Scaled-down physical modeling of seismic surveys has been done at the University of Calgary Geoscience Department for many years (Cheadle et al., 1985). The original system used stepper motors and chain-and-sprocket mechanisms to move transducers. Positioning repeatability was poor due to excessive mechanical backlash. Software for motion control and data acquisition, written in the QuickBasic language and executed on a desktop computer running under MS-DOS, became obsolete by the early 2000s. Thus, both the hardware and the software components of the original modeling facility needed significant upgrading. We decided in 2005 to completely redesign and rebuild the facility. The Positioning System The new positioning system employs modern linear electric motors with sophisticated motion controllers from Parker Motion Corporation. Eight linear motors with digital position encoders and motor drives are configured in a two-gantry orthogonal motion system. Each gantry has 4 motors. Two of these motors move the gantry in the X direction. The two remaining motors are mounted on the gantry so as to move an equipment carriage in the Y and Z directions. The eight motors on the two gantries are controlled through a controller board installed in a desktop PC running the Windows XP operating system. Transmitting and receiving transducers that generate and detect ultrasonic seismic pulses can be mounted interchangeably on the two gantry carriages and be moved by computer commands precisely and independently in three orthogonal directions. Positioning accuracy and repeatability are better than 0.1 mm. Figure 1 shows the two gantries, AC power switches and fuses, the eight motor drives, and the motor controller all mounted on a steel frame. The frame is 1500 mm long by 1200 mm wide by 1000 mm high, and scaled-down physical models with smaller dimensions can be placed within the frame beneath the gantries. After installation on the frame, the maximum ranges of motion for the X, Y, and Z motors are 1000 mm, 800 mm, and 160 mm, respectively. The standard model scale factor is 1:10, so that these dimensions represent a real-world volume 10.0 km by 8.0 km by 1.6 km. Piezoelectric Transducer Arrays For generating and detecting ultrasonic seismic waves, we use piezoelectric transducers called piezopins. A piezopin consists of a very small cylindrical piezoelectric element (approximately 1 mm diameter by .5 mm long) bonded to the tips of thin metal tubes (about 1.6 mm diameter by 150 mm or 19 mm long).
- Geophysics > Seismic Surveying > Seismic Processing (0.89)
- Geophysics > Seismic Surveying > Seismic Modeling (0.88)
- Geophysics > Seismic Surveying > Surface Seismic Acquisition > Land Seismic Acquisition (0.54)
- Information Technology > Software (1.00)
- Information Technology > Hardware (0.76)
SUMMARY In this paper we develop a method of 3D inversion of tensor electric and magnetic field data in induction well-logging applications. Our method is based on the integral equation EM field formulation. An efficient Fr´echet derivative computation is achieved by applying the modified Born approximation. The inversion method is tested on several synthetic models. The results of inversion show that both magnetic and electric tensor components can be used in 3D inversion about a single borehole. INTRODUCTION We describe a method of 3D inversion of the tensor (multicomponent) induction well-logging data, applicable to both electric and magnetic field tensors. There is growing interest in developing advanced techniques for 3D interpretation and imaging of induction well-logging data from a single borehole. It was demonstrated in several publications (Kriegshauser et al., 2001; Zhdanov et al., 2004; Wang et al., 2003; Abubakar et al., 2006 ) that, the tensor induction well-logging (TIWL) instrument can be used both for studying the anisotropy of the formations penetrated by the borehole and for imaging 3D structures in the borehole vicinity. Gribenko and Zhdanov, 2007a, presented a method of 3D nonparametric inversion of the TIWL magnetic field data, based on localized quasi-linear (LQL) approximation (Zhdanov et al. 2004) and on rigorous updates of the domain electric field (Cox and Zhdanov, 2008). In this work we extend our interest to not only the magnetic field but also to the electric field components generated by the magnetic dipole transmitters. We introduce a new rigorous method of TIWL data inversion based on integral equation (IE) forward modeling (Hurs´an and Zhdanov, 2002). The Fr´echet derivative calculation is based on the modified Born approximation, which has been proven to be an effective and accurate technique for EM data inversion (Gribenko and Zhdanov, 2007b). As a result, the IE-based method of TIWL inversion requires just one forward modeling at every iteration step, which dramatically speeds up the computations and results in a relatively fast and economical inversion method. To obtain a stable solution of a 3D inverse problem we apply regularization method (Tikhonov and Arsenin, 1977) with an option of focusing stabilizing functional (Portniaguine and Zhdanov, 1999). This stabilizer helps generate a sharp and focused image of anomalous conductivity distribution. We use regularized conjugate gradient method (Zhdanov, 2002) to minimize parametric functional. A new algorithm for 3D TIWL data inversion is tested on several models of typical 3D structures located in the vicinity of the borehole. One of the synthetic models considered in this paper is similar to the oil-water contact modelpresented by Abubakar et al. (2006). ELECTRIC AND MAGNETIC INDUCTION TENSORS Figure 1 shows schematically a TIWL instrument, containing three orthogonal transmitter coils and three orthogonal receivers. Figure 1 also shows the relations between the axes x0;y0; z0 of the instrument coordinate frame and the axes x;y, and z; of the medium coordinate frame. The angle a between z and z0 is a relative deviation of the instrument with respect to the medium, and angle b is the so-called relative bearing angle.
- Africa > South Africa > Western Cape Province > Indian Ocean (0.25)
- North America > United States > Texas > Crockett County (0.24)
- Africa > South Africa > Western Cape Province > Indian Ocean > Bredasdorp Basin > Block 9 > EM Field (0.99)
- North America > United States > Texas > Permian Basin > Central Basin > Cox Field (0.93)
- Asia > Turkmenistan > Aspheron Ridge > Cheleken Contract Area > Cheleken Field > Dzhygalybeg Field (0.93)
Summary We present and discuss the properties of a time-domain CSEM (Controlled Source ElectroMagnetic) technology that utilizes vertically oriented transmitters and receiver antennas. The data are recorded in transient mode, wherein voltage time-series are recorded after transmitter switch-off. A square pulse with an alternating polarity is followed by a silent period in which the response is measured. The response curves from many pulses are averaged in order to reduce noise, and then binned into time windows. From theory, the vertical electric field is sensitive to deep resistive layers. At late times the vertical electric field decays like Ez(t) ~t-5/2 over a rock of uniform conductivity. Another model, with the same overburden resistivity but with a resistive layer gives rise to a faster temporal decay, with a maximum contrast occurring typically at t=2-10s depending on the depth of the resistivity layer (hydrocarbons). Introduction Various CSEM methods have been developed in the last two decades (Edwards, 2005). The seabed logging method (SBL) (Ellingsrud et al., 2002) has been used extensively for the last decade in hydrocarbon exploration. It uses a horizontal dipole towed over a grid of horizontal receivers, each of them with two horizontal electrical lines perpendicular to each other. The signal has given frequencies and long offsets (distance between transmitter and receiver) are used. Vertical dipoles have already been used in the MOSES (Magnetometric Off-Shore Electrical Sounding) method (Edwards et al., 1985) with magnetic measurements in frequency-domain. However, this method is not particularly sensitive to resistive layers. Using a vertical dipole and vertical receiver for marine borehole measurements has been suggested by Scholl and Edwards (2007). An offshore, time domain EM method that uses vertical, stationary transmitters and receivers has been developed by the Norwegian geophysical company Petromarker. Short offsets in the range of 500 to 1500m are used to probe the electrical near-field that results from turning off a source current. The SBL technology that is based on the horizontal transmitter-horizontal receiver setup, measures a large electromagnetic wave directly through the sea, and a smaller signal from the underlying rock. The vertical current resulting from a vertical transmitter, is sensitive to horizontal resistive layers, and therefore carries information about the deeper structures. Technology overview The Petromarker pulsing system technology consists of two pulse generators working in parallel with a total capacity of 5000A, each transmitter dipole has a current capacity of 2500 A and consists of two electrodes attached to the vessel with cables. The lower pulse electrode, connected to the pulse cable, is positioned on the seabed. The position of the lower electrode is measured by averaging the positional data from an acoustic transponder attached to the lower pulse electrode. The vessel is moved to a position directly above the stationary lower electrode and the upper electrode is lowered 50m below sea surface, and placed so that verticality is achieved. A square pulse with alternating polarity followed by a silent period (pause) is used in this time domain method. The transmitter signal changes sign in sequences of 8 pulses (so-called P8 sequence), which is a Thue-Morse sequence (Allouche and Shallit, 1999).
- Europe > Norway > Norwegian Sea > Vøring Basin > License 218 > Block 6707/10 > Aasta Hansteen Field > Luva Field > Nise Formation (0.99)
- Europe > Norway > Norwegian Sea > Vøring Basin > License 218 > Block 6706/12 > Aasta Hansteen Field > Luva Field > Nise Formation (0.99)
- Europe > Norway > Norwegian Sea > Vøring Basin > License 218 B > Block 6707/10 > Aasta Hansteen Field > Luva Field > Nise Formation (0.99)
- Europe > Norway > Norwegian Sea > Vøring Basin > License 218 B > Block 6706/12 > Aasta Hansteen Field > Luva Field > Nise Formation (0.99)
Summary Induced polarization (IP) is widely used in oil and gas exploration in the former Soviet Union, Russia, and China. Good results from hydrocarbon exploration were achieved in China recently by applying high-power spectral induced polarization (SIP) with exploration depth exceeding the buried depth of reservoirs. Precision synchronization between the transmitter and receiver is required for the amplitude spectrum and phase spectrum of SIP measurement in the current technology. The synchronization based on the GPS disciplined oven controlled oscillator (OCXO) is the usual method applied in the transmitter and receiver which are used for SI Pexploration. The method increases weight and cost of the receiver because the GPS-disciplined OCXO uses the major part of the power consumption of the receiver. Furthermore, this method can not satisfy the measurement requirements of SIP in ocean-bottom conditions because of the lack of GPS signal. We put forward a measurement method of relative phase spectrum (RPS) to resolve the above problem. The IP information of a target is acquired by the amplitude spectrum and RPS of the complex resistivity. The method can decrease power consumption of the receiver by 50% because the RPS measurement does not require synchronization circuit between the receiver and transmitter. The RPS curve shape is similar to that of phase spectrum based on comparing typical parameters of the Cole-Cole model. The RPS owns the same IP information as the phase spectrum. In fact, the RPS formula proposed by here is equal to the phase spectrum formula which is linearly corrected to EM coupling. This was proven through a field experiment. The 3D SIP acquisition can be realized at low cost in the surface, the well, and the ocean-bottom if the phase spectrum measurement is replaced by the RPS measurement. It may expand the application of SIP in oil and gas exploration. Introduction The relative phase spectrum (RPS) is closely related to the phase spectrum and the suppression of EM coupling in IP phase measurement. Spies (1983) introduced the progress of geo-electrical exploration in the former Soviet Union after he visited there. Geophysicists of the former Soviet Union put forward a formula that corrects the EM coupling of the IP phase by phase measurements of the 1st and 3 harmonic of a rectangular wave (Spies, 1983). Hallof (1974) found that the phase shift caused by EM coupling increases approximately linearly with frequency for a uniform or layered earth. Zonge and Wynn (1975) presented a method for removing EM coupling accurately through complex resistivity measurements. Wang et al. (1985) put forward a formula to correct PFE measurements with EM coupling effects, and presented a case history with good application results. The RPS formula presented by our research has a similar effect for removing EM coupling as the formula offered by the former Soviet Union geophysicist. It linearly corrects the phase spectrum with the EM coupling effect. The hydrocarbon search using the IP method experienced a zigzag process in China. The high tide of activity was witnessed in the 1980s in China because of encouragement from the success in the former Soviet Union.
Summary In this paper we present a new approach to the interpretation of the marine controlled-source electromagnetic (MCSEM) data in areas with rough bathymetry. This approach is based on a new formulation of the integral equation EM modeling method in models with inhomogeneous background conductivity. The developed technique allows us to incorporate known geological structures and bathymetry effects in the method of iterative EM migration/holographic imaging and inversion. This approach provides us with the ability to precompute only once the effect of a known geoelectrical structure (e.g., the bathymetry effect) and keep it unchanged during the entire modeling and migration process. The method is illustrated by numerical examples of modeling and inversion of marine CSEM data in areas with rough bathymetry. Introduction During recent years, the marine controlled-source electromagnetic (MCSEM) method has become widely used for active geophysical surveying of sea-bottom geological structures in hydrocarbon exploration. The interpretation of MCSEM data over complex 3D geoelectrical structures is a very challenging problem. This problem becomes even more complicated in areas with rough sea-bottom bathymetry, because the relief of a sea bottom makes a profound effect on the EM data observed by the receivers located in close proximity to the bottom. In this paper we introduce a new approach to interpretation of MCSEM data in areas with rough bathymetry. This approach is based on a new formulation of the integral equation (IE) EM modeling method in models with inhomogeneous background conductivity (Zhdanov et al., 2006). The developed technique allows us to incorporate known geological structures and bathymetry effects in the method of iterative EM migration/holographic imaging and inversion. This approach provides us with the ability to precompute only once the effect of the known geoelectrical structure (e.g., the bathymetry effect) and keep it unchanged during the entire modeling and migration process. Taking into account that precomputing the bathymetry effect constitutes the most time-consuming part of the EM modeling, this approach allows us to increase the effectiveness of the interpretation of the MCSEM data significantly Accounting for bathymetry using EM migration with the inhomogeneous background conductivity (IBC) method A marine CSEM survey typically consists of an array of receivers, which record the response of the earth to EM signals transmitted by single or multiple transmitters. Figure 1 illustrates the principles of EM migration in a model with inhomogeneous background conductivity (IBC). We consider a 3D geoelectrical model with horizontally layered (normal) conductivity sn, inhomogeneous background conductivity sb = sn + ?sb within a domain Db, and anomalous conductivity ?sa within a domain Da (Figure 1). The model is excited by an EM field generated by an arbitrary transmitter which is time-harmonic as e. The EM field is measured by a set of electric and/or magnetic field receivers, as shown in Figure 1. The goal is to develop a method of migration of the EM field recorded by the receivers in order to generate an image of the anomalous conductivity distribution. According to the basic principles of the integral equation method with inhomogeneous background conductivity (IE IBC (Zhdanov et al., 2006)