System and method for real-time quality control for downhole logging devices

1. A method for assessing acquisition system status for a down hole device, the method comprising:

collecting acquisition system data from a plurality of sensors down hole and up hole;

applying a set of rules to the acquisition system data to obtain an acquisition quality indicator indicating quality of the acquisition data wherein the set of rules is formed from an initial training set of inputs and outputs;

creating new rules by machine learning by tracking imaging system data and field service engineer corrective actions during imaging operations; and presenting the acquisition quality indicator at a surface location.

2. The method of claim 1 , further comprising:

providing corrective action to adjust the acquisition system as indicated by the acquisition quality indicator.

3. The method of claim 1 , wherein the rules are contained in an expert system.

4. The method of claim 1 , wherein the rules are contained in a neural network.

5. The method of claim 1 , wherein the acquisition system data are dynamically weighted based on the rules.

6. The method of claim 5 , wherein the acquisition quality indicator is set to normal when a down hole tool shows a guard electrode current which exceeds a defined limit and a formation resistivity data value indicates low resistivity in the formation else the acquisition quality indicator is set to alert when the down hole tool shows the current which exceeds the defined limit and the resistivity data value does not indicate low formation resistivity.

7. A system for assessing acquisition system quality of a down hole formation evaluation system, the system comprising:

a processor in data communication with a non-transitory computer readable medium containing instructions stored therein for causing a computer to perform;

a computer program stored in the non-transitory computer readable medium, the computer program comprising instructions to collect diagnostic system data from a plurality of sensors down hole;

instructions to apply a set of rules to the acquisition system data to obtain an acquisition system quality indicator indicating quality of the acquisition data, wherein the set of rules is formed from an initial training set of inputs and outputs, the computer program further comprising instructions to create new rules by machine learning by tracking acquisition system data and field service engineer corrective actions during data acquisition operations; and

instructions to present the acquisition system quality indicator at a surface location.

8. The system of claim 7 , the computer program further comprising instructions to provide corrective action to adjust the acquisition system quality indicated by the acquisition system quality indicator.

9. The system of claim 7 , wherein the rules are contained in an expert system.

10. The system of claim 7 , wherein the rules are contained in the computer program selected from the group consisting of a neural network computer program and a fuzzy logic computer program.

11. The system of claim 7 , wherein the acquisition system data are dynamically weighted based on the rules.

12. The system of claim 11 , wherein the image quality indicator is set to normal when a down hole tool shows a current consumption exceeding a limit and a formation resistivity data value indicates low resistivity in the formation else the data acquisition indicator is set to alert when the a down hole tool shows a current consumption exceeding a limit and the resistivity data value does not indicate low resistivity.

13. A method for assessing acquisition system status for a down hole device, the method comprising:

collecting acquisition system data from a plurality of sensors down hole and up hole;

applying a set of rules to the acquisition system data to obtain an acquisition quality indicator indicating quality of the acquisition data, wherein the set of rules is formed from an initial training set of inputs and outputs;

creating new rules by machine learning by tracking imaging system data and field service engineer corrective actions during imaging operations wherein the set of rules is formed from an initial training set of inputs and outputs; and

presenting the acquisition quality indicator at a surface location.

14. The method of claim 13 wherein the acquisition quality indicator is set to normal when a down hole tool shows a guard electrode current which exceeds a defined limit and a formation resistivity data value indicates low resistivity in the formation else the acquisition quality indicator is set to alert when the down hole tool shows the current which exceeds the defined limit and the resistivity data value does not indicate low formation resistivity.

15. A system for assessing acquisition system quality of a down hole formation evaluation system, the system comprising:

a processor in data communication with a non-transitory computer readable medium;

a computer program stored in the non-transitory computer readable medium for causing a computer to perform a method, the computer program comprising instructions to collect diagnostic system data from a plurality of sensors down hole; instructions to apply a set of rules to the acquisition system data to obtain an acquisition system quality indicator indicating quality of the acquisition data; and instructions to present the acquisition system quality indicator at a surface location, wherein the set of rules is formed from an initial training set of inputs and outputs, the computer program further comprising instructions to create new rules by machine learning by tracking acquisition system data and field service engineer corrective actions during data acquisition operations.

16. The system of claim 15 , wherein the acquisition system data are dynamically weighted based on the rules.