SYSTEM FOR MONITORING REAL- TIME FLOW ASSURANCE OCCURRENCES

Abstract

The present invention addresses to a real-time flow assurance occurrence monitoring system with the aim of reducing oil production losses caused by occurrences in the flow assurance area, which uses a web tool to integrate results of simulations of multiphase flow and thermodynamic simulators with production data and specific correlations, developed to monitor the formation of deposits or blockages in subsea lines. This tool has the specific objective of monitoring the formation of hydrates, paraffins and emulsions in real time and other occurrences that may cause a production shutdown. Based on this information, it issues an alert of the occurrence in the control rooms of the operational units, supporting decision-making on operational procedures that must be carried out to avoid the loss of oil production. It further records the operations carried out to mitigate occurrences. All data is structured in tables and graphs and can be exported to other systems.

Claims

1. A SYSTEM FOR MONITORING REAL-TIME FLOW ASSURANCE OCCURRENCES, characterized in that it comprises a hydrate formation monitoring panel, a paraffin formation monitoring panel, a shutdown occurrence monitoring panel, an emulsion formation monitoring panel, pigging and soaking reports and a panel with identification of the nodal points of inorganic scale in the thermo-hydraulic profile, interconnected to the integrated E&P database (BDIEP), with automatic search of well data and integrated with the Multiphase Flow Rate Meter (MFM) that uses the flow simulator together with the Intelligent Production Surveillance (IPS) and the PI server, to predict risks of occurrences of blockages of flow assurance.

2. THE SYSTEM according to claim 1, characterized in that the integrated E&P database presents a hierarchy of the operating unit, asset, platform and well, and a production information system.

3. THE SYSTEM according to claim 1, characterized in that the multiphase flow rate meter (MFM) displays the reading of the pressure x temperature profiles generated every 5 minutes and the reading the simulator model for loading the geometry and nodal points.

4. THE SYSTEM according to claim 1, characterized in that the intelligent production surveillance (IPS) shows an indication of the probability of hydrate formation and contextualization for reading the information in the PI (full path of the well).

5. THE SYSTEM according to claim 1, characterized in that the PI server displays data reading from the PI WEB API.

6. THE SYSTEM according to claim 1, characterized in that the number of shut-down occurrences is counted by means of the available waiting time (AWT).

7. THE SYSTEM according to claim 3, characterized in that the nodal points are the chemical injection mandrel, WCT, DHSV, SESP, lift gas valve and SPU.

8. THE SYSTEM according to claim 1, characterized in that it monitors the pressure drop resulting from the formation of emulsions.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The present invention will be described in more detail below, with reference to the attached figures which, in a schematic way and not limiting the inventive scope, represent examples of its embodiment. In the drawings, there are:

[0055] - FIG. 1 illustrating a curve of pressure versus temperature, representing the favorable conditions for the formation of hydrates;

[0056] - FIG. 2 illustrating a screen of the tool showing the panels of hydrates and paraffins;

[0057] - FIG. 3 illustrating a representation of the system architecture;

[0058] - FIG. 4 illustrating an example of the curves used to define the conditions for monitoring paraffin formation and the critical deposition zone (hatched area).

DETAILED DESCRIPTION OF THE INVENTION

[0059] The system according to the present invention comprises a hydrate formation monitoring panel, a hydrate occurrence probability report, a paraffin formation monitoring panel, a shutdown occurrence monitoring panel, reports of pigging and soaking operations, an emulsion formation monitoring panel and a panel with identification of nodal points of inorganic scale in the thermo-hydraulic profile.

[0060] The monitoring panels for the formation of hydrates, paraffins and emulsions were developed in a tool that integrates production data with risk predicting systems for the occurrence of flow assurance blockages. This tool is coupled to the integrated E&P base with automatic search of well data and integrated with the MFM (Multiphase Flow Rate Meter) that uses the Marlim flow simulator. A graphical interface was developed to visualize the results through curves and tables. FIG. 3 shows the representation of the system architecture. Occurrences are monitored by operational unit, asset, platform and/or well and can be compared.

[0061] The development of panels in the tool aims at monitoring and preventing occurrences of loss of load and formation of deposits in subsea production lines and facilities in real time. The tool allows the opening of several well screens, shows the state of the wells (open and closed), the important production variables for the evaluation of flow assurance and compares the occurrences in wells on the same platform.

Hydrates

[0062] The formation of gas hydrates is the most recurrent cause of blockages and promotes greater losses in oil production, which are around 10,000 bbl/d. These losses are related to production shutdown time and operational procedures for intervention of wells.

[0063] In order to reduce oil losses due to the formation of hydrates in production systems, a panel was created to monitor and prevent the formation of hydrates in subsea production lines and facilities. This panel monitors in real time the pressure and temperature data obtained by the sensors of the operational units, simulated in MARLIM and available in the multiphase flow rate meter (MFM), the results of the thermodynamic simulations used to predict the formation of hydrates and data from the fluids and calculates the formation probability. As output data, there is the probability of occurrence depending on the depth (thermo-hydraulic profile), which is presented in table and graph format.

[0064] The calculation of the probability of occurrence was defined based on the history of hydrate formation in production fields and follows the steps below: [0065] 1. Acquisition of MFM simulation data (pressure and temperature) using the Marlim simulator; [0066] 2. Obtaining the hydrate curve by thermodynamic simulation (pressure and temperature); [0067] 3. Interpolation of the temperature in the curve; [0068] 4. Calculation of sub-cooling along the production profile of the production line (PL) - difference between the fluid temperature and the dissociation temperature for each pressure along the flow profile; [0069] 5. Definition of well sub-cooling, the highest sub-cooling value of the PL production profile; [0070] 6. Use of the defined reference sub-cooling scale to calculate the probability of hydrate formation (from -5° C. to 15° C.); [0071] 7. Use of BS&W as a correction factor in the hydrate formation probability scale, when BS&W is less than the critical BSW.

[0072] It should be noted that the scale defined for calculating the probability is being used by all wells, but the tool allows the configuration of adjustments according to the scenario. A record of available waiting time (AWT) for each well was also included. This is the time, after a production shutdown, that the operation can wait without risk of blockage. After this period, some procedure to prevent the occurrence must be carried out. The AWT tag was recorded in the IPS for signaling and alerting after a production shutdown.

Paraffins

[0073] Due to the complexity of the paraffin deposition process and the errors associated with the mathematical simulation of the occurrence, the oil properties and operational variables responsible for the occurrence in the production lines were defined based on history. Based on this information, a criterion was defined to indicate the critical zone of paraffin formation in the production line. In addition, all field operational variables are monitored in order to better predict occurrences in the near future through the variables with the greatest impact (machine learning).

[0074] The oil properties that have a direct influence on the pumping and flow conditions of the produced fluids are monitored: API density, viscosity, WAPT (Wax Appearance Point Temperature) and CDT (Critical Deposition Temperature). An extrinsic property, water content (BS&W), is also relevant for flow assurance and the potential for paraffin deposition. Based on these properties, some assumptions were defined for monitoring paraffin deposition: [0075] Registration of WAPT data, 2.sup.nd crystallization event and oil CDT; [0076] Monitoring of the thermal profile of the flow when the T.sub.flow < CDT per well; [0077] Monitoring flow and GOR (SIP data) x time; [0078] Use of T.sub.flow (MFM) , T.sub.wall (MFM) , CDT x line length to identify the critical region of paraffin deposition.

[0079] For the definition of the critical deposition zone, the following assumptions were adopted: [0080] 1) T.sub.flow < CDT [0081] 2) T.sub.ambient < T.sub.flow

[0082] This information is consolidated in the form of graphs and tables. The hatched area in FIG. 4 represents the critical deposition region on the production line, according to the assumptions adopted.

[0083] In the paraffin panel, the curves with the flow rate data (Q) x gas-oil ratio (GOR) x total gas-liquid ratio (TGLR) are also displayed. For wells without lift gas, only the GLR is reported (GLR = Qg/(Qo+Qw)).

[00001]$\begin{array}{l}\text{TGLR calculation formula}=\left(\text{GLR*}\left(\text{Qo}\left(1-\text{BSW}\right)\right)\right)+\\ \left(\text{Qo*GOR}\right)/\left(\text{Qo/}\left(1-\text{BSW}\right)\right)\end{array}$

[0084] The consolidated information is useful in identifying wells with paraffin deposition potential, in quickly identifying regions of the line most susceptible to deposition based on the assumptions adopted, in the constant evaluation of assumptions based on operational history and, from a structured database (pigging/soaking reports), in the identification of other operational parameters that have a possible impact on the deposition process through analysis of now structured data (influence of flow rate, GOR, GLR, etc.).

[0085] The consolidation of these data and the consequent improvement in the assessment of the deposition risk help in monitoring the phenomenon and in the assertiveness of mitigation procedures, with an impact on the reduction of production losses, and will be used in machine learning to define of new monitoring assumptions.

Emulsions

[0086] The evaluation of emulsion formation in producing fields is monitored in the system by: [0087] BS&W values over time; [0088] Instability in production (graph of pressure variation as a function of time); [0089] Calculation of pressure drop as a function of time; [0090] Reynolds number information; [0091] Information on the presence of free water; [0092] Calculation of the oil gain potential with the destabilization of the emulsion; [0093] Visualization of simulations in Marlim of the fluid without and with emulsion using viscosity data obtained in the laboratory; [0094] Table with information and check list.

[0095] Some monitoring criteria were established, such as: pressure differential between pure and emulsified oil flow greater than 7%, BS&W greater than 30%, Reynolds number greater than 10.sup.5, absence of free water, among others. Consolidated information is used to select wells with the greatest potential for oil gain through the use of flow-enhancing products and is exported to other applications.

Shutdown

[0096] The occurrence of production shutdowns whose time is longer than the available waiting time (AWT) implies the need to carry out a hydrate prevention procedure. Accounting for the number of shutdowns that exceed the AWT in a given period, for the same well, is an indication of the probability of hydrate blockage (the more frequent these occurrences, the greater the chances of hydrate formation).

[0097] In addition, this monitoring is capable of contributing to production development designs, estimating operational efficiency based on the application of prevention procedures, as well as EFS studies for the application of a new technology, since it is possible to quantify production losses per well in these operations.

[0098] The data with this information are presented in bar graphs and tables.

Inorganic Scales

[0099] The thermo-hydraulic profiles obtained by the tool were associated with other databases to show the points with the greatest potential risk of scale formation (nodal points). The mapped nodal points are: chemical injection mandrel, WCT, DHSV, SESP, lift gas valve and SPU, among others. Pressure and temperature data at each of these points are available in table form for export to the MultiScale simulator. Total losses of flow assurance

[0100] The total losses of flow assurance will be quantified by an algorithm that will use the MFM simulation to calculate the theoretical flow rate and the flow rate calculation by the pressure variation in the choke to calculate the actual flow rate. This concept is related to the overall loss by the system (scaling, intermittency, emulsion) except hydrate, where there is no partial loss.

Pigging and Soaking Operations

[0101] The pigging and soaking operations are carried out to remove paraffin deposits along the subsea line.

[0102] In the developed tool, the reports of pigging and soaking operations were customized based on operational experience separating the steps of planning, execution and evaluation of results. The types of fluids used, the type, size and supplier of the pigs and the most used process variables were predefined, but the system allows the customization of this information.

[0103] The operations registration form includes the dates and times of start and end of operations, step by step, information on fluids and pigs and has free fields for notes. Operations can be compared and reports sent in different formats. There is a modal of graphs referring to PIG operations (number of losses per pass, reason for losses per pass, efficiency of PIG passes, number of passes, pig integrity, among others).

EXAMPLES

[0104] The following examples are presented in order to more fully illustrate the nature of the present invention and the way to practice the same, without, however, being considered as limiting its content.

[0105] The tool contains a panel for each occurrence, based on the important field variables and the specific algorithms that were defined, but it also integrates the information for a panoramic view of the occurrences. The hydrate formation monitoring panel shows the moment when the pressure and temperature conditions of the fluids in production enter the hydrate phase envelope in real time. The pressure and temperature curves obtained in the MFM (with real data) and the predicted curve of hydrate formation by thermodynamic simulation are compared with updates every 5 minutes (FIG. 2). Based on these curves, the probability of formation of hydrates is calculated considering a scale of sub-cooling defined through accumulated experience, based on occurrences over the years of the operator.

[0106] The graph of pressure versus temperature, the graph of the probability of occurrence versus the length of the subsea line for visualization in the region of greatest risk and the probability scale are presented. The data is also presented in tabular form and can be easily exported to other systems. The tag of hydrate formation probability for each well was recorded in the Intelligent Production Surveillance (IPS) system. In the IPS, assumptions were defined for the alert of occurrences that are visualized by the operators in the panels of the control room. When the probability is considered high, starting from a defined value, there is an alert and the operators follow the established procedures to prevent the occurrence. Subsequently, the gain with the anticipation of information about the occurrence is quantified.

[0107] In the paraffin panel, oil characterization data obtained in the laboratory (WAPT, 2.sup.nd event and CDT) and fluid and ambient temperature data are presented. This information is evaluated within the occurrence criticality criterion defined in paragraph [0061] and appears highlighted in a hatched area in the graph (FIG. 4). The flow rate values and gas-liquid ratio are also presented. All data is displayed in graphs and tables and can be printed or exported to other systems.

[0108] In the emulsions panel, pressure drop as a function of time with the increase in BS&W and previously defined checklist items are monitored. The information from several wells is compared and from these data the wells with the greatest potential for oil gain with the subsea injection of demulsifier are selected.

[0109] It should be emphasized that the gains related to this invention are: [0110] .Math. Anticipation of knowledge of the occurrence; [0111] .Math. Reduction of production losses related to the formation of hydrates and paraffins; [0112] Increased operational efficiency; [0113] Reduction of decision-making time; [0114] Identification of alternatives to increase production; [0115] Integrated view of occurrences; [0116] Obtaining a history of structured cases for future machine learning work to adjust probability calculation scales or include new boundary conditions.

[0117] Considering that the losses related to flow assurance occurrences are very high, with the anticipated and integrated information of the occurrences in a single environment, it is expected to reduce the current production losses. A reduction of just 10% of these losses (around 25,000 bopd) already promotes a benefit of around 45 million USD/year (25,000 bopd × 10% × 365 × 50 USD/barrel).

[0118] It should be noted that, although the present invention has been described in relation to the attached drawings, it may undergo modifications and adaptations by technicians skilled on the subject, depending on the specific situation, but provided that within the inventive scope defined herein.