Weak signal detection is very important in the downhole acoustic telemetry system. This paper introduces the Duffing oscillator weak signal detection method for the downhole acoustic telemetry systems. First, by solving the Duffing equation, analyzed the dynamics characteristic of  Duffing oscillator and  weak signal detection principle; and then on this basis, built Duffing oscillator circuit  based on the Duffing equation, by circuit simulation to study the Duffing circuit sensitive to different initial parameters, conducted a detailed analysis for how the different parameters impacted the system statuses and the low-pass filter with simplicity and availability was proposed for signal demodulation. The results show that the method could effectively detect the weak changes of input signal and suppress strong noise; it is feasible, advanced and practical used for downhole acoustic telemetry system

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Abstract-To obtain new ways of detecting weak signals, we analyzed the motion of a Duffing oscillator in different input states by solving the Duffing equation and then elaborating on the basic principles of weak signal detection based on Duffing oscillator phase-change characteristics. The experiment that shows how to achieve weak signal detection with a Duffing oscillator based on virtual instrument technology and then discusses the impact on signal detection coming from Gaussian white noise and how to implement weak signal detection with noise. The results show that a Duffing oscillator not only can be effective for detection of weak signals in the background of strong noises, but it also has high performance to cost ratio to achieve it with virtual instrument technology. Compared to existing methods, it can greatly improve the detection results and has broad application.

The parameter calculation relating to petroleum reservoir characterization and lithologic identification based on RBF neural networks is studied in this paper. Two models for reservoir permeability prediction and lithologic identification have been constructed and are applied to predict the unknown samples. The prediction result of reservoir permeability has a higher consistency with the practical cases. The parameter prediction and lithologic identification precision have been greatly improved compared to the traditional BP neural networks. The results show that the RBF neural network is very promising for the application of petroleum reservoir characterization.

This paper reviews the development of ground and underground communications in drillstring, and analysis the current information transmission method used in several problems and limitations. Pointed out the information and the power transmission is an important part of the intelligent drillstring and put forward sharing a pair of embedded wires to transmit information and power at the same time new solutions. Intelligent drillstring with embedded wires transmission method can transmit enough power from the ground to the underground, but also can establish the ground and underground two-way "information superhighway" with maximum transmission rate of 500Kbps at the same time, conducted a ground simulation test, obtained the expected results, which shows the feasibility and superiority of the intelligent drillstring.