Dejun Liu

Vertical magnetic field and its analytic signal applicability in oil field underground pipeline detection

We propose using the vertical component of the magnetic anomaly (vertical magnetic field (VMF)) and its analytic signal (AS) to detect oil field underground pipelines. The connection between two peaks of the VMF curves or the AS curves was used to calculate the pipeline azimuth, and the peak coordinates of the AS were used to determine the horizontal position of pipelines. Then, the effect of the pipeline magnetization direction and pipeline buried depth on the horizontal locating error was analyzed. Three typical pipeline models were used for verifying this method. Results indicate that this method can be used to precisely calculate the stretch direction of the pipeline and effectively improve the identification capability in detecting parallel pipelines. The horizontal position of the pipeline axis can be accurately located by the peak of the AS and the locating error increases with the increase in pipeline buried depth, but it is not affected by pipeline outer diameter, thickness, susceptibility. The instrument design and the VMF measurement strategy are realistic and applicable. The VMF detection with its AS provides a new effective method for horizontal locating and direction calculating of oil field underground pipelines.

Magnetic anomaly inversion using magnetic dipole reconstruction based on the pipeline section segmentation method

In the model of a horizontal straight pipeline of finite length, the segmentation of the pipeline elements is a significant factor in the accuracy and rapidity of the forward modeling and inversion processes, but the existing pipeline segmentation method is very time-consuming. This paper proposes a section segmentation method to study the characteristics of pipeline magnetic anomalies—and the effect of model parameters on these magnetic anomalies—as a way to enhance computational performance and accelerate the convergence process of the inversion. Forward models using the piece segmentation method and section segmentation method based on magnetic dipole reconstruction (MDR) are established for comparison. The results show that the magnetic anomalies calculated by these two segmentation methods are almost the same regardless of different measuring heights and variations of the inclination and declination of the pipeline. In the optimized inversion procedure the results of the simulation data calculated by these two methods agree with the synthetic data from the original model, and the inversion accuracies of the burial depths of the two methods are approximately equal. The proposed method is more computationally efficient than the piece segmentation method—in other words, the section segmentation method can meet the requirements for precision in the detection of pipelines by magnetic anomalies and reduce the computation time of the whole process.

A study on directional resistivity logging-while-drilling based on self-adaptive hp-FEM

Numerical simulation of resistivity logging-while-drilling (LWD) tool response provides guidance for designing novel logging instruments and interpreting real-time logging data. In this paper, based on self-adaptive hp-finite element method (hp-FEM) algorithm, we analyze LWD tool response against model parameters and briefly illustrate geosteering capabilities of directional resistivity LWD. Numerical simulation results indicate that the change of source spacing is of obvious influence on the investigation depth and detecting precision of resistivity LWD tool; the change of frequency can improve the resolution of low-resistivity formation and high-resistivity formation. The simulation results also indicate that the self-adaptive hp-FEM algorithm has good convergence speed and calculation accuracy to guide the geologic steering drilling and it is suitable to simulate the response of resistivity LWD tools.

An artificial bee colony-based SLM scheme for PAPR reduction in OFDM systems

Orthogonal frequency division multiplexing (OFDM) signal has a high momentary peak-to-average power ratio (PAPR), since it is superimposed by many independent subcarriers. Because it does not cause distortion and is easy to realize, the selected mapping (SLM) scheme is a very attractive one among various PAPR reduction solutions. However, conventional SLM (C-SLM) scheme has unbearable computational complexity. In this paper, a novel artificial bee colony-based SLM scheme (ABC-SLM) is proposed. Simulation results show that the proposed algorithm can get good PAPR reduction and has a low computational complexity.

The time-domain equalization research of underground high-speed cable transmission based on OFDM and its realization in DSP

The high-rate communication service is increasingly in line with public demand whether in the field of wireless communication or wired communication. The Orthogonal Frequency Division Multiplexing (OFDM) has gradually received wide attention in recent years due to its advantages of high bandwidth efficiency as well as capability of anti-interference and anti-multipath; besides, its modem technology can also improve the logging cable transmission rate. This article is based on technologies of channel estimation and time domain equalization in OFDM systems of underground cable transmission, and conducts simulation of channel estimation and time domain equalization algorithms on MATLAB software to test its practicability. The two algorithms are transplanted to the hardware DSP algorithm as a way to realize the time domain equalization of collected data. Simulation results show that: the channel estimation and time domain equalization methods can recover the distorted signal to original signal with high precision.

Numerical studies of imaging subsurface waterfloods using CSERT with time-lapse inversion

During the operation of the waterflooding technique, it is necessary to identify the waterflooding areas to enhance oil displacement efficiency. A casing-surface electrical resistivity tomography (CSERT) system using a well casing as a long electrode is able to detect a wide lateral scope, but its vertical resolution and ability to identify deep anomalies in the reservoir are limited, particularly for reservoirs with high-conductivity anomalies in the shallow subsurface, which disturb the response from the water floods at depth. In this study, we first simplified this kind of reservoir into a dual layered anomaly model. Then the log–inject–log method with time-lapse inversion was proposed and evaluated regarding its ability to improve the imaging of the deep waterflooding areas and the shallow anomaly. The results were compared with the commonly used static measurement with static inversion. In the static inversion results, the shallow anomaly was imaged well but the deep anomaly was unobservable. The results of the proposed log–inject–log method with time-lapse inversion showed that it is able to identify the shallow and deep anomalies better under various conditions, thus validating its ability to improve the vertical resolution of the CSERT system.