KR20220137745A - Mooring buoy with data transmission system - Google Patents

Abstract

At least one mooring buoy for mooring a hydrocarbon storage vessel, comprising: a base portion configured to be moored to the seabed and coupled to a first fluid transmission line; a movable turntable rotatable with respect to the base portion and adapted to be coupled to the second fluid transmission line; a fluid swivel between the base portion and the turntable for coupling the first fluid transmission line and the second fluid transmission line; at least one sensor for sensing at least one parameter, such as an environmental parameter, a fluid transmission line flow parameter, and/or an operating parameter; a processing unit coupled to the at least one sensor, embodied to process the at least one parameter; and a remote communication unit configured to transmit the at least one parameter to a web server.

Description

Mooring buoy with data transmission system

The present invention relates to a mooring buoy for mooring a vessel, in particular a hydrocarbon storage vessel, wherein the buoy is embodied to be moored to the seabed and is rotatable with respect to a base portion coupled to a first fluid transmission line and a second fluid a mooring portion or turntable coupled to the transmission line, wherein the mooring buoy includes a fluid swivel between the base portion and the turntable for coupling the first fluid transmission line and the second fluid transmission line, the buoy comprising: and a plurality of sensors for sensing at least one of a parameter, a fluid transmission line flow parameter, and an operating parameter. The invention also relates to a system comprising such a mooring buoy.

Such moored buoys are as known from the prior art and are typically used to transport fluids such as hydrocarbon fluids between a processing site, for example a hydrocarbon process plant or process platform, and a tanker as a loading buoy, or as an offloading buoy. Used for reverse flow between tankers and offloading buoys. The base part of the buoy is usually provided with at least one, preferably a plurality of anchor points to which the anchor lines are connected, which at their other ends are connected to the seabed via anchors, thus fixing the base part to the seabed.

The base part is embodied to be coupled to at least one fluid transmission line (hard pipe or resilient hose), such as a riser connected to a subsea installation pipeline for transporting hydrocarbons to and from the buoy. At the connections of submerged pipelines and transmission lines, there may be a submerged valve station (PLEM) capable of regulating hydrocarbon fluid flow through hydraulic and/or electrically activated valves. The submerged station is activated via an umbilical cable that connects the submerged station and the buoy and may include electrical signal and/or hydraulic lines for measurement, activation and control purposes of the submerged station.

On the stationary buoyancy base part a rotatable mooring part, or a so-called turntable, is preferably connected via a rod carrying bearing arrangement. The turntable is provided with one or more mooring points for connecting a mooring line (hawser) to the tanker vessel. The bearing between the base part and the turntable allows the tanker vessel moored through the hawser to the turntable and with the turntable around the base part moored to the stationary seabed due to environmental forces and conditions such as ocean currents and/or wind. connected to the weather vane.

More preferably, the turntable of the buoy comprises a pipe, preferably a hard pipe, which can be coupled to a second fluid transmission line, which is generally a suspended hose assembly, which at its other end carries hydrocarbon fluid to the tanker vessel and It may be connected to a tanker vessel for transmission from a tank vessel.

A movable mooring or turntable is coupled to the substantially stationary base portion, and the mooring portion is rotatably coupled to the base portion. More preferably, the buoy is provided with a fluid swivel and sometimes an additional field-optical or signal swivel. The swivel is preferably arranged on the vertical centerline of the buoy and load carrying bearings. The stator part of the swivel is fixed to the base part of the buoy and the rotor part, which is connected to the stator part of the swivel through a small bearing, and is connected to the turntable of the buoy. The stator portion of the fluid transfer swivel is coupled to the first fluid transfer line, and the rotor portion of the fluid transfer swivel is coupled to the turntable of the buoy.

Hydrocarbon fluid may be transferred from the offshore station to the tanker vessel through a subsea installation pipeline, a first transmission line, a fluid swivel and a second transmission line to fill the tanker vessel, or for unloading purposes a reversed fluid stream is transferred to the tanker vessel. It can be built as an offshore station from

When a submersed station (PLEM) is placed between an underwater pipeline and a transmission line, the umbilical actuating the submerged station is connected to an electro-optical swivel, which transmits signals, electricity and sometimes hydraulic power to turntables and subsea installation equipment. transfer between The field-optical swivel is usually placed on the turntable of the buoy. Umbilicals are generally provided with electrical cables, signal transmission cables and hydraulic transmission conduits for data and/or power transmission from subsea installed submerged stations to buoys and vice versa.

Such mooring buoys are typically provided with a so-called remote telemetry unit (RTU) which is implemented to collect and transmit a plurality of parameters such as environmental parameters, fluid transmission line flow parameters and operating parameters. The buoy is provided with a plurality of sensors for measuring parameters and a UHF radio transmitter or modem for transmitting the parameters attached. The motion of the buoy or the transfer of fluid through the fluid transmission line can then be adjusted based on the measured parameters. Typically, the umbilical is provided with electrical cables, signal cables and hydraulic transmission conduits for data and/or power transmission from the subsea-mounted submerged station to the buoy's turntable and vice versa.

The telemetry unit is typically wirelessly connected to a master telemetry unit (MTU), which may be located onshore at the processing site. For example, the MTU may be coupled to a plant management system such as a Supervisory Control And Data Acquisition (SCADA) system. The telemetry unit of the moored buoy may also be connected wirelessly with a portable telemetry unit (PTU), for example for the transmission of information between the moored buoy and the vessel moored (to be moored) on the buoy.

It is, among other things, an object of the present invention to provide a more reliable, improved and/or multifunctional mooring buoy for mooring ships.

This object is met, first of all, by a mooring buoy according to claim 1 . More specifically, this purpose is, among other purposes, as at least one mooring buoy for mooring a hydrocarbon storage vessel,

- a base portion embodied to be anchored on the seabed and adapted to be coupled to the first fluid transmission line;

- a movable turntable rotatable with respect to the base portion and adapted to be coupled to the second fluid transmission line;

- a fluid swivel between the base portion and the mooring portion for coupling the first fluid transmission line and the second fluid transmission line;

- at least one sensor for sensing at least one parameter, such as an environmental parameter, a fluid transmission line flow parameter, and/or an operating parameter;

- a processing unit coupled to the at least one sensor, embodied to process the at least one parameter; and

- and a remote communication unit configured to transmit said at least one parameter to a web server.

Compared to known buoys as described above, an improved moored buoy is obtained when the remote communication unit is implemented to be connected to a web server, or generally a remote server, for transmitting at least one parameter to said server. The data transmitted to the server is preferably made available to other user clients as well. In contrast, prior art moored buoys typically use a telecommunication unit comprising a UHF radio transmitter or UHF modem for transmitting parameters to an adjacent telemetry unit as described above. The communication distance and bandwidth of these remote communication units are limited.

The telecommunication unit is embodied to be coupled to transmit at least one parameter, preferably a plurality of parameters. The sensor may be implemented to measure at least one of rotation, tilt and roll and axial displacement of the buoy along the x, y and z directions. Preferably, all parameters are measured. Accordingly, a plurality of sensors may be implemented.

The telecommunication unit is preferably implemented to transmit the parameter via the cellular data network. Preferably, the telecommunication unit is configured to transmit a cellular network transmitter and transmit at least one parameter to the server via a cellular communication system. Preferably, the telecommunication unit comprises a 3G, 4G and/or 5G-transmitter or the like. Any authenticated device connected to the cellular network may also receive the parameters.

Additionally or alternatively, the remote communication unit comprises a satellite communication unit. The unit may be provided with a suitable antenna or dish for communicating with a non-terrestrial network or a satellite-based network. Especially in remote areas, this ensures that the data generated from the buoy is readily available to the web server.

According to a preferred embodiment, the remote communication unit is implemented to connect to a remote server via the Internet or preferably another wide area network. The web server may be configured to transmit and receive content in response to incoming requests conforming to a Hypertext Transfer Protocol (HTTP) or File Transfer Protocol (FTP) protocol or other suitable type of network protocol. The remote communication unit is then implemented to transmit the parameter to the remote server, or otherwise make the parameter available at the remote server. The remote server may also be accessible by other connected remote devices. Additionally or alternatively, any remote device may be connected directly to the telecommunication unit of the mooring buoy. For example, the mooring buoy may host a web server that may be accessible via the Internet or similar network. The remote user client can then connect to the buoy to access the data.

According to a preferred embodiment, the processing unit further comprises a storage unit for at least temporarily storing the at least one parameter. A storage unit, for example in the form of a memory means or a computer memory, for example a large-capacity USB memory, can store the parameter measured by the at least one sensor. The stored data may, for example, be transmitted to the web server at predetermined intervals and/or upon request of the web server.

Thus, the storage unit may, for example, perform more complex processing using parameters measured during a certain period of time, as well as store the parameters for later transmission. If the buoy is further provided with a radio transmitter as described below, this may be the case, for example, if at a certain point in time the vessel is not nearby to receive any transmitted parameters. Then, when the vessel is within a certain distance, the stored parameter, or a plurality of parameters, can now be transmitted using the radio transmitter.

According to a further preferred embodiment, the processing unit is implemented to process the at least one parameter obtained from the server, in order to generate time series data. For example, the processing unit may associate a date and time stamp with each measurement value obtained from the sensor, and store the data in the storage unit. Preferably, the processing unit is implemented to process a plurality of parameters to generate time series data of the parameters.

Preferably, the processing unit, eg its storage unit, comprises a data historian server, which enables recording and retrieval of production and sensor data obtained by the sensor over time. . Preferably, it stores the information in a time-series database that stores data efficiently with minimal disk space and can be retrieved quickly. Moreover, non-time series information can be incorporated within the data historian to provide context. One of the important advantages of a data historian server is that it can correlate data over time. The data historian server may provide well-organized and easily accessible operational data.

Preferably, the time series data or database is made accessible via a remote communication unit. As mentioned above, this may be the case when a remote user client connects to the buoy and accesses the stored data, for example via the web. However, it would be advantageous if the remote communication unit was implemented to transmit time series data of at least one parameter, preferably to a remote server as mentioned above. Therefore, instead of sending the data to the master telemetry unit (MTU) as described above, the parameter data is sent to a web server, where the data can be analyzed. Thus, the web server can function as a virtual MTU.

Any vessel connected to (to be connected to) the buoy, eg a tanker, can generally access the parameters using a web server as mentioned above or via a remote communication unit. However, it would be desirable if the remote communication unit was further implemented to be coupled to transmit data via conventional wireless transmission. Therefore, it is more preferable that the telecommunication unit comprises a UHF radio transmitter. The time series data may be transmitted through a wireless transmitter. However, since the actual parameter values are relevant during loading or unloading of the vessel via the buoy, the telecommunication unit is preferably implemented to transmit live data of at least one parameter.

According to a further preferred embodiment, the processing unit The processing unit is embodied to operate in a storage mode for generating the time-series data and a streaming mode for transmitting the parameter using the telecommunication unit. In the streaming mode, the sensor data obtained by the sensor is preferably transmitted directly using a telecommunication unit. The storage mode and the streaming mode may be active at the same time. Preferably, the processing unit is implemented to initiate the streaming mode upon request, for example via a web server or generally via a telecommunication unit. Preferably, the processing unit is implemented to initiate the streaming mode upon request from the remote communication unit, in particular upon request via a wireless transmitter. More preferably, the processing unit is arranged to initiate said streaming mode when connecting a vessel to said telecommunication unit.

Thus, the processing unit may be implemented to process the data to be stored in a time series manner, for example using a data historian server as mentioned above, and to transmit any parameters received from the sensor directly via the telecommunication unit. can It would be advantageous if the processing unit was implemented to analyze at least one parameter in order to process the data, for example to generate time series data as mentioned above. The processing unit may process the parameter and send the second parameter to the remote communication unit and/or the storage unit based on the received parameter.

According to a further aspect, the processing unit comprises a microcontroller-based processing unit. Processing and analysis of sensor parameters, or sensor data in general, may then occur, at least in part, on the buoy itself. Instead of collecting and directly transmitting raw sensor data, ie parameters measured by at least one sensor, raw sensor data can be processed and preferably analyzed within the buoy. Preferably processing the sensor data comprises preprocessing the raw sensor data for transmission, for example to generate time series data as mentioned above. The processed parameters can then be transmitted using the remote communication unit. Processing the data on-board in a buoy, ie the base part or turntable, allows more relative parameters to be transmitted, for example to a master telemetry unit or a portable telemetry unit as described above. Then, local processing and further processing of the data may no longer be required. Moreover, preferably transmitting processed data instead of raw data reduces the required bandwidth of the telecommunication unit. Alternatively, data post-processing may also be performed on a remote server where the data is collected and stored.

It is a disadvantage of known moored buoys as described above that the telemetry unit, or any coupling between the sensor and the telecommunication unit, is exposed to wear. Typically, such telemetry systems include a programmable logic controller (PLC). Although these PLC-based systems are typically robust, it has been found that the circumstances imposed on the mooring buoys according to the present invention are too stringent. Therefore, the processing unit preferably comprises a microprocessor, preferably a microcontroller-based processing unit. Using a microcontroller-based processing unit instead of a PLC-based unit, for example, allows more complex calculations and processing.

The microcontroller, or microprocessor, is preferably implemented on a suitable printed circuit board that is coupled to the different inputs and outputs using suitable digital interfaces. The interface may be coupled to a sensor, a telecommunication unit and/or a storage unit. The processing unit may include, for example, a tablet or similar electronic device. Preferably, the processing unit is embodied in a suitable casing, preferably a double-layer casing. The processing unit including the casing preferably has at least an IP67 waterproof and dustproof function. The microcontroller-based unit is then less exposed to wear in harsh environments.

The microprocessor may be any conventional general purpose single-chip or multi-chip microprocessor, such as manufactured by Intel®, AMD®, or similar companies. Preferably, the processing unit is a non-PLC based processing unit.

Although the buoy provided with the microprocessor-based processing unit is preferably further equipped with a remote communication unit implemented to connect to a web server, such a buoy may be equipped with only a remote communication unit for wireless communication only. The processed data may then be transmitted via a wireless modem, for example to a ship or MTU.

Preferably, the buoy comprises a first bearing configured to allow rotation between the base part and the turntable. The second bearing may then comprise a fluid swivel for coupling the fluid transmission line as mentioned above. A further preferred embodiment is for transmitting optical and/or electrical signals between the base part and the turntable, for example for transmitting signals between the subsea installation equipment and the turntable, preferably in the base part and the field-optical cable It further includes a signal or field-optical swivel having a stator part connected and a rotor part connected to the turntable. The signal swivel is preferably coupled to the processing unit. The processing unit may then be implemented to actuate any submersible equipment such as a PLEM or general purpose valve as mentioned above.

According to a further aspect, the buoy according to the invention is embodied for operation in a moored buoy system comprising at least one buoy and a remote server. The buoy and the server, preferably the web server, are preferably in contact via the Internet or other wide area network as described above.

The system preferably comprises an analysis server configured to provide operational parameters indicative of the operation of the buoy. According to a preferred embodiment, the analysis server is implemented to calculate the sensed or determined at least one parameter, the at least one operating parameter indicative of the operation of the associated hardware, such as a buoy or a connected fluid transmission line. The operating parameters may be made available to the user, for example using a web server as mentioned above, preferably using a secure login.

The analysis server may be implemented within the buoy, for example within its processing unit. The processing of the data then takes place within the processing unit of the mooring buoy. The remote device may retrieve any of the determined operating parameters or general operating data from the processing unit, eg any storage thereof, for example via a remote server as described above. The operating parameters, or in general operating data, can then be transmitted by the remote communication unit. This reduces bandwidth usage. Therefore, instead of using a physical master telemetry unit as known in the prior art, the processing unit of the mooring buoy can process the data.

However, it would be desirable if the web server includes, or at least connects to, an analytics server. Then, the processing unit of the buoy does not require high computational power. It is also possible for both the buoy and the remote server to include an analysis server.

Preferably, the analysis server is implemented to receive a plurality of parameters from the sensor to obtain sensor data. It is mentioned herein that sensor data may include parameters obtained from a plurality of sensors over a period of time. Accordingly, the sensor data may further include historical data, in particular time series data as mentioned above. Preferably, the data comprises at least one of rotation, tilt and roll and axial displacement of the buoy along the x, y and z directions.

It may also be possible for the analysis server to be implemented to receive at least one external parameter, the analysis server processing said external parameter, preferably in combination with any of the parameters sensed by the sensor, to determine an operating parameter, and implemented to analyze. Then, the local sensor data of the buoy obtained by the plurality of sensors may be combined with the global data, ie, external parameters received by the analysis server. If so, more reliable operating parameters can be determined and transmitted. External parameters may include, for example, weather conditions.

According to a further preferred embodiment, the analysis server is implemented to determine the operating parameters using a predictive model or algorithm. For example, an operating parameter may indicate an event, such as a predicted failure or other malfunction of any process or equipment associated with the buoy. The operating parameters can then be determined efficiently and reliably. Note that the term predictive model herein may include a predictive model, such as a regression model, but may further include a classification model or a clustering model.

The predictive model may be at least one of a neural network, a random forest, a k-nearest neighbor classifier, a logistic regression model, a k-means clustering model, a support vector machine, or any other suitable machine learning model. . Selecting the type of predictive model, where applicable, may determine whether the model is at any suitable distance or (ratio) such as Euclidean distance, Minkowski distance, Jaccard dissimilarity measure, dynamic time warp, etc. It may further comprise combining with a similarity measure.

Then, the analysis server is implemented to determine the operating parameter based on the predictive model. Specifically, the analysis server,

- acquiring sensor data from at least one sensor;

- obtaining a trained predictive model implemented to predict or classify a motion parameter value; and

- It is preferably implemented to provide operating parameters, based on the trained predictive model and sensor data.

Then, the analysis server is preferably implemented to send the operating parameters, and to make the provided operating parameters available through the web server.

Although the trained predictive model may already be available, e.g. stored on the server, the analytics server may also:

- provide predictive models; and

- To obtain a trained predictive model, obtain a trained predictive model by training the predictive model using sensor data.

Thus, to be specific, a predictive model, which is a model that has not yet been trained, is obtained, which can be subsequently trained using sensor data and optionally other data.

Preferably, providing the predictive model comprises selecting a type of model. Selecting the predictive model may further include selecting a predetermined hyper-parameter, the predetermined hyper-parameter including a parameter defining a setting of the predictive model. It will be understood by those skilled in the art of predictive modeling that hyperparameters will depend on the type of predictive model, the type of data, the predictive parameters that the model seeks to find, and other conditions. To give examples of hyperparameters: the number of neighbors (k) in the k-nearest neighbor classifier, the number of layers and nodes/hidden units (and connections between nodes) in the neural network, the number of support vectors in the support vector machine, k - The number of clusters in the mean clustering model, etc. Other examples of hyperparameters are learning rate, training implementation size, and number of training epochs.

Preferably, at least the training of the model takes place on a centralized server, for example a web server. The analytics server is then implemented to receive sensor data from the buoy, eg raw and/or preprocessed data as mentioned above. This data is then used to train a predictive model and make this trained model available through a web server.

If the buoy is provided with an analysis server, the analysis server of the buoy may be implemented to receive the trained predictive model, preferably via a web server. This may take place via a remote communication unit. As mentioned above, the telecommunication unit is implemented to connect to a wide area network, such as the Internet. The trained predictive model may be stored on a remote server, preferably a remote Internet server, and the remote communication unit is then implemented to receive the trained predictive model from the remote server and provide the model to the processing unit. Then, the training of the model can take place on a web server where sufficient computational power is available, while the prediction of the operating parameters can take place on the buoy itself.

As mentioned above, providing operational parameters may also occur at the web server. The trained predictive model is then run on a web server, which receives sensor data, preferably time series data, from the buoy. The analysis server is then configured to receive sensor data from the at least one buoy and provide operational parameters based on the received sensor data.

Preferably, the analysis server is implemented to store a plurality of predictive models. The predictive model may be implemented, for example, to define a plurality of different operating parameters for the buoy. Examples of parameters include mooring line fatigue, hawser condition, bearing and submersible hose condition. The analysis server may be implemented to obtain a plurality of predictive models, and to define a plurality of operational parameters or generally operational data based on the trained predictive model. The predictive model may be trained using sensor data obtained from a plurality of sensors of the buoy.

It is usually difficult to obtain reliable (ie trained to be reliable) predictive models. According to a further aspect, there is provided a mooring buoy system comprising a web server and a plurality of buoys, preferably having a substantially similar configuration. Then, the analysis server is preferably implemented to receive sensor data from a plurality of buoys. For example, sensor data of other mooring buoys of the same type may be received at the analytics server, configured to train a predictive model or provide operating parameters based also on the received sensor data from a plurality of buoys. is implemented

As an alternative, a model trained using data from one buoy can be used to determine parameters for another buoy. Then, the analysis server is preferably configured to train a predictive model based on data derived from one buoy, and to use this model for another buoy, or on another buoy. Preferably, the analysis server is now implemented to receive, ie obtain, sensor data from a mooring buoy as described above, the sensor data comprising data generated by the sensor for sensing at least one parameter of said buoy. . The analytics server is now

- provide a predictive model; and

- It is preferably implemented to train a predictive model using sensor data to obtain a trained predictive model.

The predictive model can then be trained in an analytics server, for example a web server, and transmitted, for example, to the at least one buoy or otherwise used for the at least one buoy. Preferably, the analytics server is configured to receive sensor data from the first buoy, train the predictive model, use the predictive model or transmit it to or for the second buoy. Also, this model may be transmitted to the first buoy or used for the first buoy.

According to a further preferred embodiment, in order to further increase the reliability of the model, the analysis server is implemented to receive sensor data from a plurality of mooring buoys. Data may be stored on an analytics server. Preferably, sensor data from a plurality of buoys is used to train the predictive model. Using data from more buoys increases the reliability of the model.

The remote server may be implemented to normalize the sensor data from the plurality of buoys, wherein the normalizing includes at least obtaining the normalized sensor data by normalizing or scaling the sensor data. In this way, the unique and unique factors for each of the individual buoys are normalized, or otherwise factored, so that these normalized data are safely combined with the (normalized) data from the other buoys in order to train a predictive model. make it possible to combine

Then, a model trained using data from a plurality of buoys can be used to determine operating parameters for one buoy by supplying sensor data from the one buoy to the model. Therefore, the analysis server is preferably implemented to provide operating parameters for the buoy, based on the trained predictive model and sensor data from the buoy.

It would be desirable if the training of the model took place on a centralized analysis server as mentioned above. Alternatively, training may take place within a buoy, specifically within its processing unit. The web server is then configured to receive sensor data from the first moored buoy and transmit the sensor data to the second moored buoy. Also, data can be transmitted directly, ie without a web server. The second mooring buoy can then use the received data to train or optimize the model. Preferably, the web server is implemented to transmit sensor data from a plurality of buoys to a single buoy. The sensor data may have already been normalized, or the data is normalized in the buoy. As mentioned, using data from multiple sources improves the reliability of the model. The web server may be implemented to receive the predictive model from the first buoy and transmit the predictive model to the second buoy.

Although using data from multiple buoys increases the reliability of the model, it has been found that grouping buoys by location and/or type of buoy and training the model accordingly provides an improved system. The plurality of buoys is then preferably divided into subgroups, for example based on location and/or type. For each group, preferably a trained predictive model is obtained by training the model using data obtained or received from buoys in each group. Then, the analysis server is implemented to train a plurality of group prediction models, each group prediction model being trained using sensor data obtained from buoys in the group. This improves reliability.

Each group prediction model may be different, for example with respect to architecture. However, it would be desirable if the analysis server were implemented to provide a general predictive model, and to provide a group predictive model by training the general predictive model using training data from each of the groups to obtain the group predictive model.

As mentioned above, a plurality of operating parameters can be obtained for a single mooring buoy. Also, a plurality of group prediction models may be obtained for different operating parameters. Grouping multiple models increases reliability.

According to a further aspect, there is provided a method for operating a buoy, mooring buoy system or analysis server as described above.

According to a further aspect, there is provided a processing unit and/or a telecommunication unit as defined above for a mooring buoy. Such a unit, preferably a combination of a processing unit and a telecommunication unit, can now be fitted to an existing buoy, converting said buoy into an improved moored buoy according to the invention.

The invention is further illustrated by the following drawings, which show preferred embodiments of the device and method according to the invention and are not intended to limit the scope of the invention in any way:
- Figure 1 shows a combination of a mooring buoy, a ship and a plant;
- Figure 2 shows a mooring buoy in perspective;
- FIG. 3 shows a cross section of the buoy of FIG. 1 along plane II;
4 schematically shows a system comprising a buoy;
5 schematically shows a system comprising a process for determining operating parameters;
6 schematically shows a system for generating a plurality of parameters; and
7 schematically shows a system of buoys divided into a plurality of groups;

1 shows a hydrocarbon fluid through a subsea installation fluid conduit or pipeline 42 and a resilient riser 41, a fluid transfer swivel 3, a floating loading or offloading hose 5 and a ship or shuttle tanker 300 A mooring buoy 1 is shown which is implemented to transmit via a hose coupling 303 mounted on . The buoy 1 comprises a base portion 10 provided with a plurality of anchor lines 11 connected to anchor points 12 (see FIGS. 2 and 3 ) arranged in the seabed 999 . A mooring or turntable 20 is coupled to the stationary base portion 10 of the buoy 1 , the turntable being rotatably coupled to the base portion 10 via a first load carrying bearing system. The turntable 20 may rotate about an axis A with respect to the base portion 10 . The turntable 20 is provided with one or more mooring points 25 for connection to the mooring hawser line 25a of the vessel 300 .

The base portion 10 is rigidly connected to the stator portion of the fluid transfer swivel 3 through pipe couplings 13a and 13b (see Fig. 3), and each of the pipe couplings is an elastic fluid transfer for transporting hydrocarbon fluids. It is coupled to a hose or so-called riser 41 . The risers 41a and 14b are coupled to a subsea installed pipeline 4 which is connected to an offshore hydrocarbon processing plant or storage tank for hydrocarbons that may be exported offshore or imported offshore, for example. Hydrocarbon fluid can be transmitted from the offshore station to the tanker vessel through a subsea installation pipeline (4), a first transmission line (41), a fluid swivel (3) and a second transmission line (5) to fill the tanker vessel, Alternatively, a reverse fluid stream may be established from the tanker vessel to an offshore station for unloading purposes. The transmission line 5 is coupled to a hose coupling 23 .

When the submerged station PLEM is arranged between the submersible pipeline 4 and the first fluid transmission line 41, the umbilical actuating the submerged station is connected to an electro-optical swivel (not shown), It transmits signals, electricity and sometimes hydraulic power between the turntable 20 and the subsea installation equipment, the field-optical swivel being generally placed on the turntable 20 of the buoy 1 . Umbilicals are generally provided with electrical cables, signal transmission cables and hydraulic transmission conduits for data and/or power transmission from subsea installed submerged stations to buoys and vice versa.

The fluid transfer swivel 3 is provided with a second bearing 31 between the stator part and the rotor part of the fluid transfer swivel 3 . The rotor part of the fluid transfer swivel 3 is connected to the turntable 20 of the buoy 1 , in this rotor part a second fluid transfer which floats on the sea and is implemented to be connected between the vessel 300 and the turntable 20 . A coupling 23 is provided for connection to the hose 5 . The base portion 10 and turntable 20 are coupled via a suitable rod bearing structure 32 capable of handling the mooring load of the vessel moored to the turntable 20 via a hawser line 25a.

The fluid transfer swivel on the buoy 1 allows hydrocarbon fluid to be transferred between the vessel 300 and the pipeline 42 on the seabed, which, when moored to the turntable 20, rotate about axis A (weathervane). The transport of the hydrocarbon fluid includes a floating hose (5), a rotating pipe section (23), non-rotating pipe sections (13a and 13b) and non-rotating pipe sections (13a and 13b) connected to a fluid transport swivel (3). It takes place through a resilient riser hose 41 that connects with a subsea installed PLEM system that has a fluid control valve and is connected to a pipeline 42 .

The buoy is further provided with a processing unit 30 , which is shown in more detail in FIG. 4 . The processing unit 30 is coupled to a plurality of sensors 32 which sense the parameters of the buoy 1 . Also coupled to the processing unit 30 is an output 33 in this example in the form of a light 33a and a horn 33b. A separate memory 34 is also provided next to the internal memory of the processing unit 30 . The GPS antenna 39b is coupled to the processing unit 30 via a suitable interface 39 .

For communication, the buoy 1 is provided with a UHF antenna 38 coupled to the processing unit 38 via a radio unit 37 . The radio unit 37 is implemented to communicate with a radio transmitter 301 of a crew member of the ship 300 , for example. Antenna 302 may be coupled to transmitter 301 . Also coupled to the processing unit 30 is a 4G router 35 provided with an antenna 36 . The router 35 connects the processing unit 30 to the Internet 1000 (see FIG. 5 ) and makes it possible to transmit data to the web server 201 .

The processing unit 30 in this example is in the form of a tablet 30 provided with an operating system, which in this example is Microsoft Windows. The processing unit 30 comprises a micro-processor 31 which in this example is an Intel Atmos® processor. Accordingly, the processing unit 30 may receive and process sensor data obtained from the plurality of sensors 32 . Specifically, the processing unit 30 is implemented to process the data obtained by the sensor to generate the time series data 1001 (see FIG. 5 ). The sensor data 1001 may be transmitted to the server 201 via the Internet 1000 using the cellular data transmitters 35 and 36 .

The processing unit 30 is also implemented to transmit the actual sensor readings via the wireless unit 37 while the time series data 1001 is exchanged via the internet 1000 between the web server 201 and the buoy 1 . . This will allow the user on the vessel 300 to read the most recent sensor readings. Transmitting the actual sensor readings is initiated by connecting the radio 301 to the radio unit 37 of the processing unit 30 .

Referring to FIG. 5 , the process of determining the operating parameter P representing the operating process of the buoy 1 will be described. The sensor 32 of the buoy 1 is implemented to register the rotation, tilt and roll of the buoy 1 , and this data is provided to the processing unit 30 . The processing unit 30 stores the sensor data as time series data, that is, the sensor data is given a time and date. This sensor data 1001 is transmitted to the web server 201 via the Internet using the remote communication units 35 and 36 . As mentioned, actual sensor readings or live sensor readings may be transmitted to the vessel 300 on request via the wireless units 37 , 38 .

The web server 201 may include a standalone software program configured to serve and receive content in response to incoming requests conforming to a Hypertext Transfer Protocol (HTTP) or File Transfer Protocol (FTP) protocol or other suitable type of network protocol. can The server 201 includes a training section 2001 and a parameter determination section 2002 . The training section 2001 is implemented to provide a predictive model 1002 which in this example is, for example, a neural network. The model 1002 has not yet been trained, so training data 1001a is provided. The training data 1001a corresponds in this example to the time series data 1001 obtained from the sensor 32 of the buoy 1 . The training data 1001a is enriched with event data, which in this example is a (proximity) mooring line failure. The augmented data are used to train the model 1002 to predict (proximity) mooring line failures in the future. After training the model 1002 , the trained model 1003 is obtained.

This trained model 1003 is transmitted 1003c and, based on the sensor data 1001 obtained from the buoy 1, parameters P (block 1004) to predict future (proximity) mooring line failures. is used in the parameter determination section 2002 to predict The parameter P is made available via a web page accessible to the user 303 via the Internet 1000 , for example.

In this example, sections 2001 and 2002 are part of the same analytics server 201 . However, it may also be possible where training and determining parameters are performed on different servers. It is also possible for the determination of the parameter P to take place within the buoy 1 . The processing unit 30 of the buoy 1 then comprises a parameter determination section 2002 . The trained model 1003 may then be made available via the Internet 1000 indicated by arrow 1003a. The trained model 1003 may be sent to the processing unit 30 of the buoy 1 , indicated by arrow 1003b .

In the example of FIG. 5 only one parameter P is determined for the buoy 1a. However, a plurality of parameters P ₁ -P ₃ , respectively corresponding to different operating parameters of the components of the buoy 1 may be determined. In the example of FIG. 6 , three sensor groups 32a - 32c each providing sensor data S ₁ -S ₃ are provided. In the manner shown in FIG. 5 , in this case three trained models (T ₁ -T ₃ ) are provided, which are based on the sensor data (S ₁ -S ₃ ) with parameters (P ₁ -P ₃ ). implemented to predict

6 shows a second buoy 1b, which has the same construction as buoy 1a. The buoy 1b sends data S ₁ -S ₃ to the web server 201 , which is combined with the data from the first buoy 1a in the data file 1001a-1001c. Thus, the data file or sensor data includes data from a plurality of buoys 1a, 1b. This data can be used to train a more reliable model (T ₁ -T ₃ ) (the training section is not shown but is similar to the section of Figure 5 or Figure 7 as described below). In this example, it is also possible that one or more trained models T ₁ -T ₃ are transmitted from the server 201 to the processing unit 30b of the buoy 1b. For example, a model T ₁ -T ₃ is trained on the basis of training data obtained from a first sub-table 1a, and this model T ₁ -T ₃ is now a parameter for a second sub-table 1b used to determine (P ₁ -P ₃ ).

As more data is available, the reliability of the model usually increases. However, it has been found that by dividing the buoys 1 into groups, a more reliable model may be obtained. 7 shows a plurality of buoys 1 positioned in different zones. The buoys 1 are grouped in zone groups A-C. Data from the plurality of buoys 1 are transmitted via the Internet 1000 to the web server 201 , which is schematically indicated at 1010 . In this example, the web server 201 has a training section in two parts. First, a generic model 1002 is provided in the model creation section 2001a, which in this example is also a neural network. This general model 1002 is then used in the model training section 2001b. By training a general model 1002 with different data sets 1001 obtained from different groups A-C, three different trained models 1003 are obtained (denoted as TA-TC). Each of these models can then be used to determine the parameters for the buoy for its respective group.

It will be appreciated that the same concept of grouping and training a general model to obtain specific data may be employed to train the model for each different operating parameters.

A person skilled in the art will readily appreciate that the various above-described methods may be performed by a programmed computer. Herein, some embodiments are also intended to cover program storage devices, for example digital data storage media, which are readable by a machine or computer and encode a machine-executable or computer-executable program of instructions. and these instructions perform some or all of the steps of the method described above. The program storage device may be, for example, digital memory, flash drives, magnetic disks and magnetic tape, magnetic storage media such as hard drives, or optically readable digital data storage media. Furthermore, the embodiments are intended to cover a computer programmed to perform said steps of the method described above.

The functions of the various elements illustrated in the figures, including any functional blocks termed “units”, “processors” or “modules,” use dedicated hardware and hardware capable of executing software such as firmware in association with appropriate software. can be provided by When provided by a processor, such functionality may be provided by a single dedicated processor, by a single shared processor, or by a plurality of separate processors, some of which may be shared. Moreover, any explicit use of the terms "unit", "processor" or "controller" should not be construed as referring exclusively to hardware capable of executing software, without limitation, digital signal processor (DSP) hardware, network processor, application specific integrated circuit (ASIC), field programmable gate array (FPGA), read only memory (ROM) for storing software, random access memory (RAM), and non-volatile storage. Other hardware of the prior art and/or customized may also be included.

The invention is further illustrated by the following preferred embodiments of the device and method.

embodiments

1. At least one mooring buoy for mooring a hydrocarbon storage vessel, comprising:

- a base portion embodied to be anchored on the seabed and adapted to be coupled to the first fluid transmission line;

- a movable turntable rotatable with respect to the base portion and adapted to be coupled to the second fluid transmission line;

- a fluid swivel between the base portion and the turntable for coupling the first fluid transmission line and the second fluid transmission line;

- at least one sensor for sensing at least one parameter, such as an environmental parameter, a fluid transmission line flow parameter, and/or an operating parameter;

- a processing unit coupled to the at least one sensor, embodied to process the at least one parameter; and

- and a remote communication unit configured to transmit the at least one parameter to a web server.

2. according to the first embodiment,

The telecommunication unit comprises a cellular network transmitter and/or a non-terrestrial communications transmitter.

3. according to the first or second embodiment,

The processing unit further comprises a storage unit for at least temporarily storing the at least one parameter.

4. according to the third embodiment,

the processing unit is configured to process the at least one parameter obtained from the sensor to generate time series data,

and the telecommunication unit is configured to transmit time series data of the at least one parameter.

5. The method according to any one of the first to fourth embodiments,

the telecommunication unit comprises a UHF radio transmitter;

and the telecommunication unit is configured to transmit live data of the at least one parameter.

6. The method according to any one of the first to fifth embodiments,

wherein the processing unit is configured to operate in a storage mode for generating the time series data and a streaming mode for transmitting the parameter using the telecommunication unit.

7. according to the sixth embodiment,

and the processing unit is configured to initiate the streaming mode when connecting a vessel to the telecommunication unit.

8. The method according to any one of the first to seventh embodiments,

wherein the processing unit comprises a microcontroller-based processing unit.

9. The method according to any one of the first to eighth embodiments,

The mooring type buoy is

an electro-optical swivel having a stator part connected to the base part and the electro-optic cable and a rotor part connected to the turntable for transmission of optical and electrical signals between the subsea installation equipment and the turntable, mooring buoys.

10. A mooring buoy system comprising at least one buoy according to any one of aspects 1 to 9 and a remote server, comprising:

the system comprises an analysis server configured to provide operational parameters indicative of operation of the buoy;

The analysis server,

- acquiring sensor data from the at least one sensor;

- obtaining a trained predictive model implemented to predict or classify the operating parameter values; and

- and based on the trained predictive model and the sensor data, configured to provide the operating parameter.

11. according to the tenth embodiment,

wherein the web server comprises an analysis server.

12. according to the tenth or eleventh embodiment,

The analysis server,

- provide a predictive model,

- By training the predictive model using the sensor data to obtain the trained predictive model,

a mooring buoy system configured to acquire the trained predictive model.

13. The eleventh or twelfth embodiment,

and the analysis server is configured to receive the sensor data from the buoy and train the predictive model using the received sensor data.

14. The method according to any one of the tenth to thirteenth embodiments,

and the processing unit is configured to receive the sensor data from the remote server.

15. The method according to any one of the tenth to fourteenth embodiments,

The system comprises a plurality of buoys,

The analysis server,

- Acquire sensor data from multiple mooring buoys;

- provide a predictive model, and

- A mooring buoy system, implemented to train the predictive model using the sensor data to obtain a trained predictive model.

16. The method according to the fourteenth embodiment,

and the analysis server is configured to provide operating parameters for the buoy based on the trained predictive model and sensor data from the buoy.

17. according to the fifteenth or sixteenth embodiment,

wherein the analysis server is configured to receive sensor data from a first moored buoy and transmit the sensor data to a second moored buoy.

18. The method according to any one of the fifteenth to seventeenth embodiments,

and the web server is configured to receive the predictive model from the first buoy and send the predictive model to the second buoy.

19. The method according to any one of the 15th to 18th embodiments,

The system is

comprising a plurality of groups of mooring buoys;

A group of mooring buoys is characterized by location and/or type,

The analysis server is implemented to provide a general prediction model and train a plurality of group prediction models based on the general prediction model,

wherein each group prediction model is trained using sensor data obtained from the buoys within the group.

20. A processing unit and/or a communication unit as defined in any one of the first to nineteenth embodiments for a mooring buoy.

21. A method for operating a buoy, analysis server, or mooring buoy system according to any one of embodiments 1-20.

The invention is not limited to the embodiment shown, but extends to other embodiments falling within the scope of the appended claims.

Claims (21)

A mooring buoy system comprising a remote server and at least one mooring buoy for mooring a hydrocarbon storage vessel, comprising:
The mooring buoy is
- a base part embodied to be moored to the seabed and adapted to be coupled to the first fluid transmission line;
- a movable turntable rotatable with respect to said base portion and adapted to be coupled to said second fluid transmission line;
- a fluid swivel between the base part and the turntable for coupling the first fluid transmission line and the second fluid transmission line;
- at least one sensor for sensing at least one parameter, such as an environmental parameter, a fluid transmission line flow parameter and/or an operating parameter;
- a processing unit coupled to said at least one sensor, arranged to process said at least one parameter; and
- a remote communication unit arranged to send said at least one parameter to a web server,
the system comprises an analysis server configured to provide operational parameters indicative of operation of the buoy;
The analysis server,
- acquiring sensor data from said at least one sensor;
- obtaining a trained predictive model implemented to predict or classify said operating parameter values, and
- a mooring buoy system, implemented to provide the operating parameter, based on the trained predictive model and the sensor data. The method of claim 1,
wherein the web server comprises an analysis server. 3. The method according to claim 1 or 2,
The analysis server,
- provide a predictive model;
- by training the predictive model using the sensor data to obtain the trained predictive model,
a mooring buoy system configured to acquire the trained predictive model. 4. The method according to claim 2 or 3,
and the analysis server is configured to receive the sensor data from the buoy and train the predictive model using the received sensor data. 5. The method according to any one of claims 1 to 4,
and the processing unit is configured to receive the sensor data from the remote server. 6. The method according to any one of claims 1 to 5,
The system comprises a plurality of buoys,
The analysis server,
- Acquire sensor data from multiple mooring buoys;
- provide a predictive model; and
- a mooring buoy system, implemented to train the predictive model using the sensor data to obtain a trained predictive model. 6. The method of claim 5,
and the analysis server is configured to provide operating parameters for the buoy based on the trained predictive model and sensor data from the buoy. 8. The method of claim 6 or 7,
wherein the analysis server is configured to receive sensor data from a first moored buoy and transmit the sensor data to a second moored buoy. 9. The method according to any one of claims 6 to 8,
and the web server is configured to receive the predictive model from the first buoy and send the predictive model to the second buoy. 10. The method according to any one of claims 6 to 9,
The system is
comprising a plurality of groups of mooring buoys;
A group of mooring buoys is characterized by location and/or type,
The analysis server is implemented to provide a general prediction model and train a plurality of group prediction models based on the general prediction model,
wherein each group prediction model is trained using sensor data obtained from the buoys within the group. 11. The method according to any one of claims 1 to 10,
wherein the telecommunication unit comprises a cellular network transmitter and/or a non-terrestrial communication transmitter. 12. The method according to any one of claims 1 to 11,
The processing unit further comprises a storage unit for at least temporarily storing the at least one parameter. 13. The method of claim 12,
the processing unit is configured to process the at least one parameter obtained from the sensor to generate time series data,
and the telecommunication unit is configured to transmit time series data of the at least one parameter. 14. The method according to any one of claims 1 to 13,
the telecommunication unit comprises a UHF radio transmitter;
and the telecommunication unit is configured to transmit live data of the at least one parameter. 15. The method according to any one of claims 1 to 14,
wherein the processing unit is configured to operate in a storage mode for generating the time series data and a streaming mode for transmitting the parameter using the telecommunication unit. 16. The method of claim 15,
and the processing unit is configured to initiate the streaming mode when connecting a vessel to the telecommunication unit. 17. The method according to any one of claims 1 to 16,
wherein the processing unit comprises a microcontroller-based processing unit. 18. The method according to any one of claims 1 to 17,
The system is
an electro-optical swivel having a stator part connected to the base part and the electro-optic cable and a rotor part connected to the turntable for transmission of optical and electrical signals between the subsea installation equipment and the turntable, Mooring buoy system. A processing unit and/or a communication unit as defined in any one of claims 1 to 18 for mooring buoys. A mooring buoy for mooring a hydrocarbon storage vessel as defined in any one of claims 1 to 19. 21. A method for operating a buoy, analysis server, or mooring buoy system according to any one of claims 1 to 20.

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