Sensor deployment for distributed acoustic sensing with noise cancellation using a reference coil
A distributed acoustic system (DAS) may include at least one laser that transmits a continuous wave (CW) light, a pulser optically connected to the at least one laser to receive the CW light from the at least one laser and form a light pulse, and a splitter optically connected to the pulser to optically split the light pulse into a plurality of light pulses. The DAS may further comprise a circulator optically connected to an output of the splitter, a sensor fiber attached to the circulator, and a reference coil disposed on the sensor fiber between the circulator and a first section. A method for using the DAS may include transmitting one or more light pulses from a laser into the DAS, generating an interrogator specific noise profile for the reference wellbore, and generating an application specific noise profile for a first sensor fiber disposed in the reference wellbore.
1. A method comprising:
transmitting one or more light pulses from a launch optoelectronics into a distributed acoustic system (DAS), wherein the DAS is at least partially disposed in a wellbore of interest and a reference wellbore;
generating an interrogator specific noise profile for the reference wellbore;
generating an application specific noise profile for a first sensor fiber disposed in the reference wellbore;
applying a noise control to measurements of a backscatter light from a second sensor fiber disposed in the wellbore of interest; and
optimizing a signal to noise ratio (SNR) of the measurements from the backscatter light.
2. The method of claim 1 , wherein the second sensor fiber is divided into a first section and a zone of interest.
3. The method of claim 2 , wherein a reference coil is disposed on the second sensor fiber between a circulator and the first section.
4. The method of claim 1 , wherein a reference coil is disposed on the first sensor fiber between a circulator and a reference path.
5. The method of claim 1 , further comprising adjusting a noise control algorithm of the DAS.
6. The method of claim 5 , wherein the noise control algorithm is a machine learning, a neural networks, an artificial intelligence, or a natural language models.
7. The method of claim 6 , wherein a feedback electronics filter, an open loop bandwidth, or a damping coefficients are used for the adjusting the noise control algorithm.
8. The method of claim 7 , wherein residual noise and artifacts are removed using the noise control algorithm.
9. The method of claim 5 , wherein the adjusting the noise control algorithm is performed by personnel.
10. The method of claim 9 , wherein the personnel remove one or more error signals within the noise control algorithm.