Event Detection Using DAS Features with Machine Learning

a machine learning and event detection technology, applied in the field of hydrocarbon production wells, can solve the problems of reducing oil production, contaminating and damage of surface equipment, and delaying substantial amounts of well production,

Pending Publication Date: 2020-06-04
BP EXPLORATION OPERATING CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0007]In some embodiments, a method of identifying events includes obtaining an acoustic signal from a sensor, determining one or more frequency domain features from the acoustic signal, providing the one or more frequency domain features as inputs to a plurality of event detecti...

Problems solved by technology

Such water inflow can cause a number of problems including erosion, clogging of wells due to resulting sand inflow, contamination and damage of the surface equipment, and the like.
Significant water production can result in the need to choke back production from the well to bring water production down to acceptable levels.
This can lead to reduced oil production, and potentially result in a deferral of substantial amounts of the production from the well.
Thus, the data at times can be skewed by variabi...

Method used

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  • Event Detection Using DAS Features with Machine Learning
  • Event Detection Using DAS Features with Machine Learning
  • Event Detection Using DAS Features with Machine Learning

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Experimental program
Comparison scheme
Effect test

first embodiment

[0183]In a first embodiment, a method of identifying events comprises: obtaining an acoustic signal from a sensor; determining one or more frequency domain features from the acoustic signal, wherein the one or more frequency domain features are obtained across a frequency range of the acoustic signal; providing the one or more frequency domain features as inputs to a plurality of event detection models; and determining the presence of one or more events using the plurality of event detection models, wherein at least two of the plurality of event detection models are different.

[0184]A second embodiment can include the method of the first embodiment, wherein the sensor is disposed within a wellbore, wherein the acoustic signal comprises acoustic samples across a portion of a depth of the wellbore.

[0185]A third embodiment can include the method of the first or second embodiment, further comprising identifying one or more event locations using the one or more frequency domain features.

[...

sixth embodiment

[0208]In a twenty sixth embodiment, a method of determining an output signal using an acoustic signal comprises: determining one or more frequency domain features from an acoustic signal, wherein the one or more frequency domain features are obtained across a plurality of lengths along a path of the sensor; providing the one or more frequency domain features as inputs to a plurality of event detection models; determining an indication of a presence of one or more events using the plurality of event detection models; providing the indication of the presence of the one or more events to a supervisory application; and determining, using the indication of the presence of the one or more events as inputs into the supervisory application, an output signal for a process or system.

[0209]A twenty seventh embodiment can include the method of the twenty sixth embodiment, further comprising: identifying one or more event locations using the one or more frequency domain features; and providing t...

ninth embodiment

[0222]A fortieth embodiment can include the method of the thirty ninth embodiment, wherein training the plurality of event identification models comprises: providing the one or more frequency domain features to a second logistic regression model of the logistic regression models corresponding to one or more event tests of the plurality of event tests where a second event is present; providing the one or more frequency domain features to the second logistic regression model corresponding to one or more event tests of the plurality of event tests where the second event is not present; and determining a second multivariate model using the one or more frequency domain features as inputs, wherein the second multivariate model defines a relationship between a presence and an absence of the second event.

[0223]A forty first embodiment can include the method of the fortieth embodiment, wherein the first multivariate model and the second multivariate model are different.

[0224]A forty second e...

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Abstract

A method of identifying events includes obtaining an acoustic signal from a sensor, determining one or more frequency domain features from the acoustic signal, providing the one or more frequency domain features as inputs to a plurality of event detection models, and determining the presence of one or more events using the plurality of event detection models. The one or more frequency domain features are obtained across a frequency range of the acoustic signal, and at least two of the plurality of event detection models are different.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application claims the benefit of and priority to International Application No. PCT / EP2018 / 082985 filed Nov. 29, 2018 with the European Receiving office and entitled “DAS Data Processing to Identify Fluid Inflow Locations and Fluid Type” as a foreign priority claim, where such application is hereby incorporated herein by reference in its entirety for all purposes.BACKGROUND[0002]Within a hydrocarbon production well, various fluids such as hydrocarbons, water, gas, and the like can be produced from the formation into the wellbore. The production of the fluid can result in the movement of the fluids in various downhole regions, including within the subterranean formation, from the formation into the wellbore, and within the wellbore itself. For example, some subterranean formations can release water that can be produced along with the hydrocarbons into the wellbore. Such water inflow can cause a number of problems including erosion, cl...

Claims

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Application Information

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IPC IPC(8): G01V1/50G01V1/28G01V1/30E21B47/14G06N7/00
CPCG01V1/307G01V1/50E21B47/14G01V2210/324G01V1/288G06N7/005G01V2210/21E21B2200/22E21B47/107E21B43/00E21B2200/20G06F30/20G06F30/28G01V1/001G01V1/282G06N7/01G01V99/005
Inventor THIRUVENKATANATHAN, PRADYUMNA
Owner BP EXPLORATION OPERATING CO LTD
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