The general idea of the research is based on the assumption that an oil well with an installed Sucker Rod Pump (SRP) emits a characteristic sound spectrum that can be assessed. Every change to the system (wear, beginning failures, etc) should be reflected in a corresponding change of the sound spectrum, creating thus a correlation. The scope of the research is to study noise, produced by a well and to find whether there is a relationship between emitted noise and a production state of the SRP. Correlation will be researched on the basis of dynamometer readings and actual production events.

Noise represents a function of dynamic behavior of fluids, gas, downhole, and surface equipment. Sound created by this system is recorded in on-line mood with the help of a special device installed on the wellhead. The noise data then are transmitted, uploaded to a server, and available for processing. The analysis of the noise is based on Fast Fourier Transform (FFT), Power Spectral Density (PSD) estimation, together with statistical tools.

This paper presents first tests that are done with the purpose to find a stroke’s signature. By signature it is meant characteristics that describe the stroke the best. They are best reporting features: PSD distribution, Noise Flatness, Root-Mean Squared, frequencies of maximum PSD, etc.

The result of performed characterization with the help of signature concept, determines a pattern of SRP acoustically. This allows further application of acoustic diagnosis of SRP that helps identify many failures (like leaking tubing, standing and travelling valves, excessive loads, worn out rods, gas-lock, buckling, etc.) before they cause major damage or production loss.

You can access this article if you purchase or spend a download.