Wells – Processes – With indicating – testing – measuring or locating
Reexamination Certificate
2002-02-15
2004-09-14
Bagnell, David (Department: 3672)
Wells
Processes
With indicating, testing, measuring or locating
C166S250010, C166S053000, C702S006000, C702S011000, C706S015000, C706S929000
Reexamination Certificate
active
06789620
ABSTRACT:
TECHNICAL FIELD
The present invention relates generally to operations performed in conjunction with a subterranean well and, in an embodiment described herein, more particularly provides a method of sensing a parameter in a well.
BACKGROUND
It is quite advantageous to be able to use a sensor to sense a downhole parameter in a well environment. Such parameters may include pressure, temperature, resistivity, pH, dielectric, viscosity, flow rate, fluid composition, etc. This information enables a well operator to maintain efficient production from the well, plan future operations, comply with regulations, etc.
Unfortunately, many problems are encountered in sensing downhole parameters. Such problems include unavailability of a downhole sensor which senses the desired parameter, unavailability of a sensor which can withstand the well environment for an extended period of time, high cost of sensors which can withstand the well environment, short lifespan of downhole sensors, and unavailability of a high accuracy and/or resolution downhole sensor.
For example, a suitable sensor for a desired parameter may be available for use at the surface, but it may not be designed for downhole use. As another example, a sensor which otherwise meets all of the requirements for a downhole application may be prohibitively expensive. Yet another example is given by the situation in which a high accuracy and/or resolution downhole sensor for the desired parameter is available, but the sensor has a limited lifespan in the well environment, thereby making it unsuitable for long term use in the well.
Situations also arise in which a formerly operational downhole sensor becomes damaged, unable to communicate with the surface, or otherwise becomes unavailable for sensing the parameter in the well. In the past, these situations have required either that the sensor be replaced in a time-consuming and expensive operation, or that the well be produced without the benefit of the information obtained from the sensor. The latter option is very undesirable, since typically the information obtained from the sensor is used to efficiently produce the well, such as by properly adjusting flow control devices in the well based at least in part on the sensed parameter, etc.
SUMMARY
In carrying out the principles of the present invention, in accordance with an embodiment thereof, a method is provided which solves the above problems in the art. The method utilizes a neural network to determine at least one downhole parameter, even though a sensor for that parameter is not operational downhole at the time the parameter is determined.
In one aspect of the invention, a method is provided in which parameters for individual zones of a well are determined without having operational sensors for those parameters downhole when the parameters are determined. Training data sets are obtained using surface sensors, varied valve positions and temporary sensors. The neural network is trained using this data. The neural network is then used to determine the downhole parameters in response to inputting the surface sensors' outputs and the valve positions to the neural network.
In another aspect of the invention, a method is provided in which a sensor's output is determined, even after the sensor has failed. Training data sets from a time prior to the sensor's failure are obtained. The training data sets include outputs of other downhole sensors, varied valve positions, etc. The neural network is trained to output the failed sensors' output (before failure) in response to inputting the other sensor's outputs and the valve positions to the neural network.
In still another aspect of the invention, a method is provided in which a downhole parameter is determined, without using a permanent downhole sensor for that parameter. Training data sets are obtained using a temporary sensor for the desired parameter, and using other sensors for related parameters. The neural network is trained to produce the temporary sensor's outputs when the other sensors' outputs are input to the neural network. Thereafter, when the temporary sensor is no longer available for the desired parameter, the neural network will determine the temporary sensor's output in response to inputting the other sensors' outputs to the neural network.
In yet another aspect of the invention, a method is provided in which a high accuracy and/or resolution sensor is used to calibrate a lower accuracy and/or resolution sensor. The calibration sensor is temporarily installed in the well along with the permanent downhole sensor. Training data sets are obtained by recording outputs of both of the sensors in the well. The neural network is trained using this data, so that the neural network outputs the calibration sensor outputs in response to inputting the downhole sensor's outputs to the neural network. After the calibration sensor is no longer available, the downhole sensor's outputs are input to the neural network, which determines the corresponding outputs of the higher accuracy and/or resolution calibration sensor.
In a further aspect of the invention, methods are provided whereby a “virtual” sensor is created downhole. That is, the output of a nonexistent downhole sensor is determined in response to inputting the outputs of other sensors, etc., to a trained neural network. In one method, the neural network is trained using the outputs of a sensor temporarily in the well with the other sensors. In another method, the sensor capable of sensing a desired parameter remains at the surface when training data is obtained. In still another method, the sensor for the desired parameter and the other sensors are at the surface when the training data is obtained. In yet another method, a sensor is not used for the desired parameter, but known values for the desired parameter, along with the outputs of other sensors, are used to train the neural network.
In a still further aspect of the invention, a method is provided wherein a combination of downhole sensors and surface sensors are used. These sensors may be used with a temporary sensor to obtain training data for a neural network, and for inputting to the neural network after training and after the temporary sensor is not available. Other pertinent information, such as valve positions, choke sizes, etc. may also be used. Downhole sensors may be advantageously positioned away from a harsh well environment where it is desired to sense a parameter, but sufficiently far from the surface that the sensors are not within a surface temperature affected zone of the well.
These and other features, advantages, benefits and objects of the present invention will become apparent to one of ordinary skill in the art upon careful consideration of the detailed description of representative embodiments of the invention hereinbelow and the accompanying drawings.
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Dennis John R.
Richardson John M.
Richardson Sandra M.
Schultz Roger L.
Storm, Jr. Bruce H.
Bagnell David
Gay Jennifer H.
Halliburton Energy Service,s Inc.
Konneker J. Richard
Richardson Sandra M.
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