METHODS AND DEVICES FOR ASSET OPTIMIZATION USING AUTOMATED WORKFLOWS
Publication Date: 2015-Jan-28
The IP.com Prior Art Database
The approach takes the form of a software solution, including data transmission protocols, data extraction protocols, data mining, data processing, logic and end user interface. Distributed data is acquired on the platform, then is processed and distributed under the form of status, alarms, zone or time selected data storage. A user interface will then enable: - Providing information based on the results of the automated calculations. - Selecting the data to be analysed - Classifying the data according to meaning - Efficiently storing the data - Combining with data from another source to provide additional information The approach can be used on Producing wells, Injection wells, geothermal wells, etc, which are equiped with downhole monitoring sensors. These sensors can be (but not limited to) distributed temperature sensors, distributed acoustic sensors, distributed strain sensors, distributed vibration sensors, distributed or single point pressure sensors.
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Attorney Docket No.: IS14.8465 METHODS AND DEVICES FOR ASSET OPTIMIZATION USING AUTOMATED
It can be important to monitor conditions in an oilfield. In subterranean wells, downhole data such as pressure, temperature, flow, and other fluid or reservoir properties can be sensed. For example, the well may include permanent completion deployed sensors or logging tools that transmit data. Real time monitoring tools may allow users to acquire real time raw data, which can be extracted from the location (whether offshore or onshore) then processed and manipulated to generate information that production engineers can use to understand flow and other behavioral characteristics of the well.
Brief Description of the Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present teachings and together with the description, serve to explain the principles of the present teachings. In the figures:
Figure 1 illustrates one embodiment of a computing system that may be used to implement the approaches described herein;
Figure 2 provides illustrations of certain target events that may be the subject of monitoring;
Figure 3 illustrates one embodiment of a data to information transformation process;
Figure 4 illustrates one system implementing a data transformation process;
Figure 5 illustrates one example user interface;
Figure 6 illustrates a user interface allowing the user to adjust filter parameters for monitoring;
 Figure 7 illustrates one embodiment of data analysis that may indicate an alarm condition;
Figure 8 illustrates another embodiment of a user interface;
Figure 9 illustrates another embodiment of a user interface;
Figure 10 illustrates a further embodiment of a user interface; and
Figure 11 illustrates an example of a visualization.
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The following detailed description refers to the accompanying drawings. Wherever convenient, the same reference numbers are used in the drawings and the following description to refer to the same or similar parts. While several embodiments and features of the present disclosure are described herein, modifications, adaptations, and other implementations are possible, without departing from the spirit and scope of the present disclosure.
Figure 1 illustrates a schematic view of a computing or processor system 100, according to an embodiment. The processor system 100 may include one or more processors 102 of varying core configurations (including multiple cores) and clock frequencies. The one or more processors 102 may be operable to execute instructions, apply logic, etc. It will be appreciated that these functions may be provided by multiple processors or multiple cores on a single chip operating in parallel and/or communicably l...