API unit calibration of gamma ray logging tools using simulated data
AssigneeHalliburton Energy Services, Inc.
InventorJames E. Galford
Life of this patent
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Abstract
Gamma ray logging tools are calibrated using gamma emissions data simulated using Monte Carlo modeling techniques. During the simulation, one or more nuclear activity zones of a formation are modeled and photon counting rates are determined. Using the simulated counting rates, an American Petroleum Institute (“API”) unit sensitivity factor is calculated. The API unit sensitivity factor is then applied to convert real logging tool counting responses into API units.
Claims19
A method for calibrating a gamma ray logging tool, the method comprising:
- simulating gamma ray emissions of a formation by:
- simulating a low activity zone of the formation and calculating a first counting rate for the low activity zone;
- and
- simulating a high activity zone of the formation and calculating a second counting rate for the high activity zone;
- calculating an American Petroleum Institute (“API”) unit sensitivity factor for a logging tool based upon the simulated gamma ray emissions, wherein the API unit sensitivity factor is calculated based upon the first and second counting rates;
- deploying the logging tool along a wellbore;
- obtaining a counting rate response of the logging tool;
- and
- converting the counting rate response to API units using the API unit sensitivity factor.
A gamma ray logging tool, comprising:
- one or more gamma ray emission sensors communicably coupled to processing circuitry that is operable to perform a method comprising:
- obtaining a counting rate response of the logging tool;
- and
- converting the counting rate response to API units using an API unit sensitivity factor obtained using any of methods 1-6.
A method for generating a gamma ray calibration model, the method comprising:
- simulating gamma ray emissions of a formation by:
- simulating a low activity zone of the formation and calculating a first counting rate for the low activity zone;
- and
- simulating a high activity zone of the formation and calculating a second counting rate for the high activity zone;
- and
- calculating an American Petroleum Institute (“API”) unit sensitivity factor for a logging tool based upon the simulated gamma ray emissions, wherein the API unit sensitivity factor is calculated based upon the first and second counting rates.
A system for calibrating a gamma ray logging tool, the system comprising:
- a logging tool having one or more gamma ray sensors therein;
- and
- processing circuitry communicably coupled to the logging tool and operable to perform operations comprising applying simulated gamma ray emission data to convert logging tool counting rate responses to American Petroleum Institute (“API”) units, wherein the conversion is achieved by:
- simulating a low activity zone of a formation and calculating a first counting rate for the low activity zone;
- simulating a high activity zone of the formation and calculating a second counting rate for the high activity zone;
- calculating an API unit sensitivity factor for a logging tool based upon the first and second counting rates;
- deploying the logging tool along a wellbore;
- obtaining a counting rate response of the logging tool;
- and
- converting the counting rate response to API units using the API unit sensitivity factor.
A system for generating a gamma ray calibration model, the system comprising processing circuitry operable to perform operations comprising:
- simulating gamma ray emissions of a formation by:
- simulating a low activity zone of the formation and calculating a first counting rate for the low activity zone;
- and
- simulating a high activity zone of the formation and calculating a second counting rate for the high activity zone;
- and
- calculating an American Petroleum Institute (“API”) unit sensitivity factor for a logging tool based upon the simulated gamma ray emissions, wherein the API unit sensitivity factor is calculated based upon the first and second counting rates.
Dependencies are inferred from the claim text.