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Title:
PROCESS OF DETERMINING AN INJECTION PERFORMANCE OF A WELL WHEN INJECTING A FLUID INTO A GEOLOGICAL FORMATION
Document Type and Number:
WIPO Patent Application WO/2024/057050
Kind Code:
A1
Abstract:
A process of determining a future injection performance of a well (20), a fluid (12) being intended to be injected from a surface network (18) into a geological formation (16) defining a reservoir (14), the injection performance providing a relationship between the flowrate and a bottom hole flowing pressure, the process comprising: a) obtaining a first set of data (VLP and bottom hole enthalpy), b) obtaining a surface network simulator, and a reservoir simulator, c) providing the reservoir simulator with a current working point of the well, d) running the reservoir simulator and obtaining updated pressure conditions in the reservoir, e) calculating a second set of data (IPR) for a next time step, f) providing the surface network simulator with the second set of data, g) obtaining the bottom hole flowing pressure for the next time step and an updated working point. The injection performance is obtained from the second set of data.

Inventors:
RODRIGUEZ MARTINEZ ALEJANDRO (FR)
Application Number:
PCT/IB2022/000535
Publication Date:
March 21, 2024
Filing Date:
September 16, 2022
Export Citation:
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Assignee:
TOTALENERGIES ONETECH (FR)
International Classes:
E21B41/00; E21B43/16
Domestic Patent References:
WO2004049216A12004-06-10
Foreign References:
US20080319726A12008-12-25
CA2691241C2014-03-25
US10012055B22018-07-03
Attorney, Agent or Firm:
ROCHER, Olivier et al. (FR)
Download PDF:
Claims:
CLAIMS

1 A process of determining a future injection performance of a well (20), a fluid (12) being intended to be injected from a surface network (18) via the well (20) into a geological formation (16) defining a reservoir (14) at a reservoir pressure intended to increase over time, the fluid (12) being injected at a wellhead (26) at a wellhead flowing pressure (WHFP) and a wellhead flowing temperature (WHFT) at which the fluid (12) is in liquid or dense phase, the fluid (12) flowing at a flowrate (Q) from the wellhead (26) to a bottom hole (28) where the fluid (12) is at a bottom hole flowing pressure (BHFP), a bottom hole flowing temperature (BHFT) and a bottom hole flowing enthalpy (BHFH), and the fluid (12) flowing at the flow rate (Q) from the bottom hole (28) into the reservoir (14), the injection performance providing a relationship between the flowrate (Q) and the bottom hole flowing pressure (BHFP), the process comprising the following steps: a) obtaining a first set of data (40) providing the bottom hole flowing pressure (BHFP), the bottom hole flowing temperature (BHFT) and the bottom hole flowing enthalpy (BHFH) as functions of the wellhead flowing pressure (WHFP), of the wellhead flowing temperature (WHFT) and of the flowrate (Q), b) obtaining a surface network simulator (42) adapted for performing a nodal analysis of the surface network (18) and the well (20), and obtaining a reservoir simulator (44) adapted for modeling flows in the reservoir (14), c) providing the reservoir simulator (44) with a current working point (46) of the well (20) comprising the wellhead flowing pressure (WHFPn), the wellhead flowing temperature (WHFTn), and the flowrate (Qn) for a current time step (tn), d) running the reservoir simulator (44) over the current time step (tn), and obtaining updated pressure conditions (Pn+i) in the reservoir (14), e) using the updated pressure conditions (Pn+i) in the reservoir (14), the wellhead flowing pressure (WHFPn) and the wellhead flowing temperature (WHFTn), calculating a second set of data (48), the second set of data (48) providing the bottom hole flowing pressure (BHFPn+i) as a function of the flowrate (Qn+i) for a next time step (tn+i), f) providing the surface network simulator (42) with the second set of data (48), and g) using the second set of data (48) and at least part of the first set of data (40), obtaining the bottom hole flowing pressure (BHFPn+i) for the next time step (tn+i ) and, using the surface network simulator (42), obtaining an updated working point (46) of the well (20) comprising the wellhead flowing pressure (WHFPn+i), the wellhead flowing temperature (WHFTn+i), and the flowrate (Qn+i) for the next time step (tn+i), wherein steps c) to g) are iterated over a plurality of time steps (tn, tn+i .. ), the process further comprising obtaining the injection performance from the second set of data (48) obtained at one of the time steps.

2.- The process according to claim 1 , wherein the fluid (12) has a composition such that the fluid (12) is at least partly liquid at the bottom hole (28) for at least a value of the wellhead flowing pressure (WHFP) comprised between 70 and 150 bars absolute, assuming a reservoir pressure of 20 bars absolute and a wellhead flowing temperature (WHFT) of 20°C.

3.- The process according to claim 1 or 2, wherein the fluid (12) has a pressure of its critical point greater than 60 bar absolute.

4.- The process according to any one of claims 1 to 3, wherein the fluid (12) comprises at least 50vol% of CO2.

5.- The process according to claim 4, wherein the fluid (12) comprises at least 80vol% of CO2.

6.- The process according to any one of claims 1 to 5, wherein the wellhead flowing pressure (WHFP) is greater than 74 bar absolute.

7.- The process according to any one of claims 1 to 6, wherein the first set of data comprises:

- a VLP table (50) providing the bottom hole flowing pressure (BHFP) and the bottom hole flowing temperature (BHFT) as functions of the wellhead flowing pressure (WHFP), of the wellhead flowing temperature (WHFT) and of the flowrate (Q), and

- an enthalpy table (52) providing the bottom hole flowing enthalpy (BHFH) as a function of the wellhead flowing pressure (WHFP), of the wellhead flowing temperature (WHFT) and of the flowrate (Q).

8.- The process according to claim 7, wherein the VLP table (50) is stored in the surface network simulator (42) and the enthalpy table (52) is stored in the reservoir simulator (44).

9.- The process according to any one of claims 1 to 8, wherein, in step e), calculating the second set of data (48) includes the following substeps: e1 ) selecting a plurality of potential values (Qn+i ,i) of the flowrate (Qn+i) for the next time step (tn+i), e2) using the wellhead flowing pressure (WHFPn) and the wellhead flowing temperature (WHFTn) of the current working point (46), the flowrate potential values (Qn+i,i) and part of the first set of data (40), obtaining values of the bottom hole flowing enthalpy (BHFHn+i,i) corresponding respectively to the flowrate potential values (Qn+u), and e3) using the values of the bottom hole flowing enthalpy (BHFHn+i,i) and the updated pressure conditions (Pn+i) of the reservoir (14), calculating values of the bottom hole flowing pressure (BHFPn+i,i) corresponding respectively to the flowrate potential values (Qn+i,i).

10.- The process according to claim 9, wherein, in substep e3), the values of the bottom hole flowing pressure (BHFPn+u) are obtained by iterative convergence until the differences between the updated pressure conditions (Pn+i) and each of the values of the bottom hole flowing pressure (BHFPn+u) match with pressure drops calculated by the reservoir simulator (44) between the bottom hole (28) and the reservoir (14).

11 .- The process according to any one of claims 1 to 10, wherein:

- in step c), the working point (46) further comprises the bottom hole flowing pressure (BHFPn) for the current time step (tn) and, in step g), the updated working point (46) further comprises the bottom hole flowing pressure (BHFPn+i) for the next time step (tn+i), or

- in step d), the reservoir simulator (44) is adapted for using the first set of data (40) in order to obtain the bottom hole flowing pressure (BHFPn), knowing the wellhead flowing pressure (WHFPn), the wellhead flowing temperature (WHFTn), and the flowrate (Qn).

12.- The process according to any one of claims 1 to 1 1 , comprising determining future injection performances of a plurality of wells, a fluid (12) or several fluids being intended to be respectively injected from the surface network (18) via the wells into at least one reservoir (14).

13.- A process of controlling at least a well (20), a fluid (12) being intended to be injected from a surface network (18) via the well (20) into a geological formation (16) defining a reservoir (14) at a reservoir pressure intended to increase over time, the fluid (12) being injected at a wellhead (26) at a wellhead flowing pressure (WHFP) and a wellhead flowing temperature (WHFT) at which the fluid (12) is in liquid or dense phase, the fluid (12) flowing at a flowrate (Q) from the wellhead (26) to a bottom hole (28) where the fluid (12) is at a bottom hole flowing pressure (BHFP), a bottom hole flowing temperature (BHFT) and a bottom hole flowing enthalpy (BHFH), and the fluid (12) flowing at the flow rate (Q) from the bottom hole (28) into the reservoir (14), the injection performance providing a relationship between the flowrate (Q) and the bottom hole flowing pressure (BHFP), the process comprising the following steps:

- obtaining a target flowrate (QT), and

- using a process according to any one of claims 1 to 1 1 , determining a needed wellhead flowing pressure (WHFP) in order to achieve the target flowrate (QT).

14.- The process according to claim 13, wherein the target flowrate (QT) is provided by the surface network simulator (42).

15.- The process according to claim 13 or 14, further comprising injecting the fluid (12) at the wellhead (26) at the needed wellhead flowing pressure (WHFP).

Description:
Process of determining an injection performance of a well when injecting a fluid into a geological formation

The present invention deals with a process of determining a future performance of a well, a fluid being intended to be injected from a surface network via the well into a geological formation defining a reservoir at a reservoir pressure intended to increase over time, the fluid being injected at a wellhead at a wellhead flowing pressure and a wellhead flowing temperature, the fluid flowing at a flowrate from the wellhead to a bottom hole where the fluid is at a bottom hole flowing pressure and a bottom hole flowing temperature, and the fluid flowing at the flow rate from the bottom hole into the reservoir, the process comprising the following steps:

- obtaining a surface network simulator adapted for performing a nodal analysis of the surface network and the well, and obtaining a reservoir simulator adapted for modeling the reservoir,

- providing the reservoir simulator with a current working point of the well for a current time step,

- running the reservoir simulator over the current time step, and obtaining updated conditions in the reservoir,

- providing the surface network simulator with the updated conditions,

- using the surface network simulator, and obtaining an updated working point of the well for a next time step, wherein some steps are iterated over a plurality of time steps.

The invention also deals with a process of controlling at least this well, comprising the following steps: obtaining a target flowrate, and using the above process for determining a wellhead flowing pressure needed to achieve the target flowrate, and possibly injecting the fluid at the wellhead at the needed wellhead flowing pressure that was determined.

Gas, such as raw natural gas, can be extracted from one or several geological formations via one or several wells. In the oil and gas field, in order to control a production well or to anticipate its future behavior, a vertical lift performance, known as “VLP”, and an inflow performance relationship, or “I PR”, are commonly used.

The VLP provides a relationship between the bottom hole flowing pressure and the flowrate of upcoming gas in the well, knowing the fluid properties, the well geometry, the thermal conductivity and vertical profile of the geological formations. The VLP accounts for phenomena occurring in the well, in particular frictional, gravity and acceleration pressure drops and heat exchanges with the environment. The IPR provides a relationship between the bottom hole flowing pressure and the flowrate of gas flowing in the well from the reservoir, knowing the reservoir pressure, and for given fluid properties, well completion geometry and temperature conditions. The IPR accounts for phenomena occurring in the well completion, in particular pressure drops.

The VLP and IPR curves cross each other at an operating point of the well providing the bottom hole flowing pressure and the flowrate. The VLP curve typically has a first decreasing section, a minimum and then an increasing section, while, in the IPR curve, the pressure decreases when the flowrate increases (for a production well).

When injecting natural gas into a reservoir instead of extracting it, the injection well is usually controlled in a similar manner using VLP and IPR curves, with the minor difference that the VLP curve typically comprises a first increasing section, a maximum and then a decreasing section, and, in the IPR curve, pressure increases when the flowrate increases.

The relationship between the bottom hole flowing pressure and the flowrate of gas flowing out the well into the reservoir could be called an “outflow performance curve”, or “OPR”. The term “IPR” is still generally used, with the meaning of “injection performance relationship” instead of “inflow performance relationship”.

Using VLP and IPR curves works well when injecting a fluid such as natural gas in a reservoir. However, it has been noted that, when injecting a fluid such as a CO2 rich fluid in liquid or dense phase at the wellhead, for example when performing CO2 capture and storage, or “CCS”, controlling the injection using the VLP and IPR curves does not work in a satisfactory manner, or does not work at all, particularly when the reservoir is deep, for example more than 3000 meters TVDSS (true vertical depth sub sea), and/or very depleted, i.e. with a rather low reservoir pressure, for example between 20 and 50 bar absolute.

An aim of the invention is thus to solve all or part of the above issues, by providing a process of determining a future performance of an injection well which performs better, in particular when the injected fluid is a CO2 rich one in view of storing CO2 in a geological formation.

To this end, the invention proposes a process of determining a future injection performance a well, a fluid being intended to be injected from a surface network via the well into a geological formation defining a reservoir at a reservoir pressure intended to increase over time, the fluid being injected at a wellhead at a wellhead flowing pressure and a wellhead flowing temperature at which the fluid is in liquid or dense phase, the fluid flowing at a flowrate from the wellhead to a bottom hole where the fluid is at a bottom hole flowing pressure, a bottom hole flowing temperature and a bottom hole flowing enthalpy, and the fluid flowing at the flow rate from the bottom hole into the reservoir, the injection performance providing a relationship between the flowrate and the bottom hole flowing pressure, the process comprising the following steps: a) obtaining a first set of data providing the bottom hole flowing pressure, the bottom hole flowing temperature and the bottom hole flowing enthalpy as functions of the wellhead flowing pressure, of the wellhead flowing temperature and of the flowrate, b) obtaining a surface network simulator adapted for performing a nodal analysis of the surface network and the well, and obtaining a reservoir simulator adapted for modeling flows in the reservoir, c) providing the reservoir simulator with a current working point of the well comprising the wellhead flowing pressure, the wellhead flowing temperature, and the flowrate for a current time step, d) running the reservoir simulator over the current time step, and obtaining updated pressure conditions in the reservoir, e) using the updated pressure conditions in the reservoir, the wellhead flowing pressure and the wellhead flowing temperature, calculating a second set of data, the second set of data providing the bottom hole flowing pressure as a function of the flowrate for a next time step, f) providing the surface network simulator with the second set of data, and g) using the second set of data and at least part of the first set of data, obtaining the bottom hole flowing pressure for the next time step and, using the surface network simulator, obtaining an updated working point of the well comprising the wellhead flowing pressure, the wellhead flowing temperature, and the flowrate for the next time step, steps c) to g) are iterated over a plurality of time steps, the process further comprising obtaining the injection performance from the second set of data obtained at one of the time steps.

In other embodiments, the process comprises one or several of the following features, taken in isolation or any technically feasible combination:

- the fluid has a composition such that the fluid is at least partly liquid at the bottom hole for at least a value of the wellhead flowing pressure comprised between 70 and 150 bars absolute, assuming a reservoir pressure of 20 bars absolute and a wellhead flowing temperature of 20°C;

- the fluid has a pressure of its critical point greater than 60 bar absolute;

- the fluid comprises at least 50vol% of CO2;

- the fluid comprises at least 80vol% of CO2;

- the wellhead flowing pressure is greater than 74 bar absolute; - the first set of data comprises: a VLP table providing the bottom hole flowing pressure and the bottom hole flowing temperature as functions of the wellhead flowing pressure, of the wellhead flowing temperature and of the flowrate; and an enthalpy table providing the bottom hole flowing enthalpy as a function of the wellhead flowing pressure, of the wellhead flowing temperature and of the flowrate;

- the VLP table is stored in the surface network simulator and the enthalpy table is stored in the reservoir simulator;

- in step e), calculating the second set of data includes the following substeps: e1 ) selecting a plurality of potential values of the flowrate for the next time step; e2) using the wellhead flowing pressure and the wellhead flowing temperature of the current working point, the flowrate potential values and part of the first set of data, obtaining values of the bottom hole flowing enthalpy corresponding respectively to the flowrate potential values; and e3) using the values of the bottom hole flowing enthalpy and the updated pressure conditions of the reservoir, calculating values of the bottom hole flowing pressure corresponding respectively to the flowrate potential values;

- in substep e3), the values of the bottom hole flowing pressure are obtained by iterative convergence until the differences between the updated pressure conditions and each of the values of the bottom hole flowing pressure match with pressure drops calculated by the reservoir simulator between the bottom hole and the reservoir;

- in step c), the working point further comprises the bottom hole flowing pressure for the current time step and, in step g), the updated working point further comprises the bottom hole flowing pressure for the next time step;

- in step d), the reservoir simulator is adapted for using the first set of data in order to obtain the bottom hole flowing pressure, knowing the wellhead flowing pressure, the wellhead flowing temperature, and the flowrate; and

- the process comprises determining future injection performances of a plurality of wells, a fluid or several fluids being intended to be respectively injected from the surface network via the wells into at least one reservoir.

The invention also proposes a process of controlling at least a well, a fluid being intended to be injected from a surface network via the well into a geological formation defining a reservoir at a reservoir pressure intended to increase over time, the fluid being injected at a wellhead at a wellhead flowing pressure and a wellhead flowing temperature at which the fluid is in liquid or dense phase, the fluid flowing at a flowrate from the wellhead to a bottom hole where the fluid is at a bottom hole flowing pressure, a bottom hole flowing temperature and a bottom hole flowing enthalpy, and the fluid flowing at the flow rate from the bottom hole into the reservoir, the injection performance providing a relationship between the flowrate and the bottom hole flowing pressure, the process comprising the following steps:

- obtaining a target flowrate, and

- using a process, determining a needed wellhead flowing pressure in order to achieve the target flowrate.

In particular embodiments, the process comprises one or several of the following features, taken in isolation or any technically feasible combination:

- the target flowrate is provided by the surface network simulator; and

- the process further comprises injecting the fluid at the wellhead at the needed wellhead flowing pressure.

The invention and its advantages will be better understood upon reading the following description, given solely by way of example and with reference to the appended drawings, in which:

- Figure 1 is a schematic, side view of an installation comprising a surface network, a well and a reservoir, defined by a geological formation,

- Figure 2 is a diagram showing the evolution of the pressure and the enthalpy of the fluid from the surface network to the reservoir shown in Figure 1 , and

- Figure 3 is a block diagram illustrating steps of determining the injection performance of the well shown in Figure 1 .

With reference to Figure 1 , an installation 10 will be described.

The installation 10 is adapted for injecting a fluid 12 into a reservoir 14 defined by a geological formation 16. The installation comprises a surface network 18, a well 20 adapted to drive the fluid 12 from the surface network to the reservoir 14, and a choke 22 for controlling the flowrate of the fluid passing in the well.

As a variant (not shown), the installation 10 may comprise a plurality of wells such as the well 20, in order to inject the fluid 12 in various parts of the reservoir 14, or in different reservoirs.

In the example, for the sake of clarity, the surface network 18 is very simple, with a source 24 of fluid under pressure and a pipeline 25 for driving the fluid 12 from the source to the choke 22.

In reality, surface networks may be more complex, with several sources, some of them supplying the fluid 12 in cryogenic state coming from ships, some of them providing the fluid in gaseous state, such as nearby industries, for example steel and cement factories. Surface networks may also comprise a network of pipelines arriving at one or several injection wells such as the well 20. Surface networks may also comprise compressors and pumps. Compressors are useful in the case of gas phase sources in order to achieve transport in liquid/dense phase. Pumps are used for adding energy to the liquid/dense phase in the pipelines.

The well 20 comprises a wellhead 26, located just downstream of the choke 22, and a bottom hole 28 located within the reservoir 14. The well 20 may comprise perforations 30 adapted for injecting the fluid 12 into the reservoir 14.

The fluid 12 is injected from the surface network 18 via the well 20 into the geological formation 16. The reservoir 14 is at a reservoir pressure intended to increase over time when the injection takes place.

The fluid 12 is injected at the wellhead 26 and has a wellhead flowing pressure WHFP and a wellhead flowing temperature WHFT just after the choke 22. In practice, the wellhead flowing pressure WHFP can be adjusted by opening or closing the choke 22. The wellhead flowing temperature WHFT is in general a consequence of the fluid temperature upstream of the choke 22 and the expansion through the choke. The wellhead flowing pressure WHFP is adjusted so that the fluid 12 is in liquid or dense phase at the wellhead 26.

The fluid 12 flows at a flowrate Q from the wellhead 26 to the bottom hole 28 where the fluid is at a bottom hole flowing pressure BHFP, a bottom hole flowing temperature BHFT and a bottom hole flowing enthalpy BHFH.

The fluid 12 flows at the flow rate Q from the bottom hole 28 into the reservoir 14. The injection performance provides a relationship between the flowrate Q and the bottom hole flowing pressure BHFP.

The fluid 12 for example has a composition such that its saturation line and its critical point stand within the operating envelope of pressures and temperatures of the well 20.

The composition is for example such that the fluid 12 is at least partly liquid at the bottom hole 28 for at least a value of the wellhead flowing pressure WHFP comprised between 70 and 150 bars absolute, assuming a pressure of 20 bars absolute in the reservoir 14 and a wellhead flowing temperature WHFT of 20°C. This does not mean that the reservoir 14 is at a pressure of 20 bars absolute, nor that the wellhead flowing temperature WHFT of 20°C; this means that the fluid 12 is such that it may be at least partly liquid at the bottom hole 28 during operation of the well 20 under certain conditions.

For example, the fluid 12 has a pressure of its critical point greater than 60 bar absolute. In a particular embodiment, the fluid 12 comprises at least 50vol% of CO2, preferably at least 80vol% of CO2, more preferably at least 90voL%, 95voL% or even 99voL% of CO2.

Figure 2 is a pressure-enthalpy diagram of the fluid 12. Pressure is at the Y axis and noted as “P”, and enthalpy is the X axis and noted as “H”. The diagram shows several zones: “S” where the fluid 12 is solid, “L” where it is liquid, “V” where it is a vapor. In a zone “L+V”, the fluid 12 is at least partly liquid and partly vapor. When its pressure P is above the pressure of its critical point, the fluid 12 is either liquid or dense (zone “D”).

For example, when it exits the source 24, the fluid 12 has a certain pressure and a certain enthalpy such that it is liquid or dense. Then the fluid 12 flows in the pipeline 25 and its pressure and enthalpy decrease. In the choke 22, the fluid 12 for example undergoes an isenthalpic expansion. Just after the expansion, at the wellhead 26, the fluid 12 is for example in the “L” zone”.

In a particular embodiment, the wellhead flowing pressure WHFP is always greater than 74 bar absolute, in order to ensure that the fluid 12 is liquid or dense at the wellhead 26.

Then the fluid 12 flows down the well 20. At the bottom hole 28, the fluid 12 may be in the “L” or “L+V” zones, meaning it can be liquid, or partly liquid, the rest being vapor.

The fluid 12 finally enters the reservoir 14, where it is stored as vapor, when the reservoir pressure is rather low, or in dense phase, when the reservoir pressure near wellbore is higher.

In reality, the reservoir 14 may be not homogenous, especially when the injection starts. Near the wellbore, the reservoir pressure usually rises faster, with a vaporization front travelling further and further from the well. If the injection is stopped for some time, the reservoir pressure tends to equalize. Once the reservoir pressure rises above the critical pressure at a given temperature, the fluid 12 is liquid or dense (usually dense because reservoirs are above 100°C in general).

As can be seen in Figure 2, when the fluid 12 flows out of the well 20 in the reservoir 14, it may be at least partly liquid.

A process according to the invention will now be described.

The goal of the process is to allow controlling the well 20 by providing a future injection performance of the well, the injection performance providing a relationship between the flowrate Q of the fluid 12 and the bottom hole flowing pressure BHFP.

The process for example includes obtaining a target flowrate QT for the fluid 12, and determining a needed wellhead flowing pressure WHFP in order to achieve the target flowrate in the well 20.

The target flowrate QT may be a function of time/evolve with time.

For example, the target flowrate QT is provided by a surface network simulator adapted for performing a nodal analysis of the surface network 18 and the well 20.

As a variant, the target flowrate QT comes from another source. According to another variant, a target well head flowing pressure WHFP is set, and a corresponding flowrate Q is determined at a given wellhead flowing temperature WHFT.

Advantageously, the process further comprises actually injecting the fluid 12 at the wellhead 26 at the needed wellhead flowing pressure WHFP.

As a variant, the fluid 12 is not injected at the needed wellhead flowing pressure WHFP, for example if the target flowrate QT was just a try and is finally not selected.

The process of determining the future injection performance of the well 20 will now be explained.

The process comprises a step a) of obtaining a first set of data 40 (Figure 3) providing the bottom hole flowing pressure BHFP, the bottom hole flowing temperature BHFT and the bottom hole flowing enthalpy BHFH as functions of the wellhead flowing pressure WHFP, of the wellhead flowing temperature WHFT and of the flowrate Q.

The process comprises a step b) of obtaining a surface network simulator 42 adapted for performing a nodal analysis of the surface network 18 and the well 20, and of obtaining a reservoir simulator 44 adapted for modeling the reservoir 14.

The process comprises a step c) of providing the reservoir simulator 44 with a current working point 46 of the well 20 comprising the wellhead flowing pressure WHFP n , the wellhead flowing temperature WHFT n , and the flowrate Q n for a current time step t n .

The process comprises a step d) of running the reservoir simulator 44 over the current time step t n , and obtaining updated pressure conditions P n+i in the reservoir 14.

The process comprises a step e) of calculating a second set of data 48, using the updated reservoir pressure conditions P n+ i, the wellhead flowing pressure WHFP n , and the wellhead flowing temperature WHFT n , the second set of data providing the bottom hole flowing pressure BHFP n+i as a function of the flowrate Q n+i for a next time step t n+ i.

The process comprises a step f) of providing the surface network simulator 42 with the second set of data 48.

The process comprises a step g) of obtaining the bottom hole flowing pressure BHFP n+i for the next time step t n+i using the second set of data 48 and at least part of the first set of data 40, and of obtaining an updated working point 46 of the well 20 using the surface network simulator 42, the updated working point comprising the wellhead flowing pressure WHFP n+ i, the wellhead flowing temperature WHFT n+ i, and the flowrate Q n+i for the next time step t n+ i.

Steps c) to g) are iterated over a plurality of time steps, the process further comprising obtaining the injection performance from the second set of data 48 obtained at one of the time steps, for example the last time step. Advantageously, the injection performance of the well 20 is contained in the second set of data 48 providing a link between the bottom hole flowing pressure BHFP n+i and the flowrate Q n+i into the reservoir 14. This link takes into account the phases distribution of the fluid 12 at the bottom hole 28 (liquid/dense, partly liquid...), which was not the case in prior art processes.

In a particular embodiment, the process includes determining future injection performances of a plurality of wells (not shown), the fluid 12 or several fluids being intended to be respectively injected from the surface network 18 via the wells into one or several reservoirs.

In step a), the first set of data 40 is for example in the form of a table (one or several arrays), and/or functions.

In a particular embodiment, the first set of data 40 comprises a VLP table 50 and an enthalpy table 52.

The VLP table 50 provides the bottom hole flowing pressure BHFP and the bottom hole flowing temperature BHFT as functions of the wellhead flowing pressure WHFP, of the wellhead flowing temperature WHFT and of the flowrate Q. The enthalpy table 52 provides the bottom hole flowing enthalpy BHFH as a function of the wellhead flowing pressure WHFP, of the wellhead flowing temperature WHFT and of the flowrate Q.

For example, the VLP table 50 is stored within the surface network simulator 42 and the enthalpy table 52 is stored in the reservoir simulator 44.

The skilled person knows how to calculate the VLP table 50 taking into account the geometry of the well 20, using a thermal model and a fluid model. In addition, the bottom hole flowing enthalpy BHFH is calculated in order to obtain the enthalpy table 52.

The first set of data 40 is advantageously calculated, or provided in advance, and does not need to be recalculated at each time step.

In step e), the second set of data 48 is for example in the form of a table (an array), or a function.

In particular embodiments, the second set of data 48 for example comprises, consists of, or is equivalent to an IPR table.

In step b), the surface network simulator 42 is known in itself, and is advantageously an integrated asset model adapted for simulating all the components of the surface network 18. For example, the surface network simulator 42 may be the GAP® module from Petroleum Experts, Ledaflow® or Pipesim®.

The surface network simulator 42 is adapted for using the second set of data 48 (the IPR table) and part of the first set of data 40 (in our example the VLP table 50) of the well 20, to solve a nodal analysis at the bottom whole 26, or each bottom hole in case of several wells, the wellhead flowing pressure WHFP being usually the control variable, and to calculate the working point 46.

The reservoir simulator 44 may be for example based on IX® from Intersect, ECL® from Eclipse, MBal® from Petroleum Experts. However, these simulators are adapted, in a manner known in itself, for iteratively use part of the first set of data 40 (in our example the enthalpy table 52) in order to calculate the second set of data 48 (an updated IPR table) at the end of each time step.

In step c), in a particular embodiment, the working point 46 further comprises the bottom hole flowing pressure BHFP n for a current time step t n . This allows passing the bottom hole flowing pressure BHFP directly to the reservoir simulator 44.

In step d), the reservoir simulator 44 flows for an entire time step at the current working point 46 provided by the surface network simulator 42.

In a particular embodiment, the working point 46 does not comprise the bottom hole flowing pressure BHFP n and the reservoir simulator 44 is adapted for using the first set of data 40, in the example the VLP table 50, in order to obtain the bottom hole flowing pressure BHFP n knowing the wellhead flowing pressure WHFP n , the wellhead flowing temperature WHFTn, and the flowrate Q n .

In step e), the reservoir simulator 44 generates the second set of data 48, which in our example is an updated IPR table, considering the reservoir conditions in the near wellbore region, particularly the updated pressure conditions P n+ i.

Advantageously, in step e), calculating the second set of data 48 (IPR table) includes three substeps e1 ), e2) and e3).

In substep e1 ), a plurality of potential values Q n+ i,i of the flowrate Q n+i is selected for the next time step t n+ i.

For example, i = 0, 1 , 2... 9, with Q n+ i, 0 = 0 and BHFP n+ i, 0 = P n+ i.

As variant, more than ten values can be used for the flowrate potential values.

The potential values Q n+i ,i may be chosen so as to cover a normal range of flowrate operating values.

In substep e2), the wellhead flowing pressure WHFP n and the wellhead flowing temperature WHFT n of the current working point 46, the flowrate potential values Q n+ u and the first set of data 40 (the enthalpy table 52 in our example) are used in order to obtain values of the bottom hole flowing enthalpy BHFH n+ u and optionally values of the bottom hole flowing temperature BHFT n+ u corresponding respectively to the flowrate potential values Q n+ i,i. If values of the bottom hole flowing temperature BHFT n+ i,i are not obtained from the first set of data 40, they can be calculated knowing the fluid properties BHFH n+ i,i and BHFP n+ i,i.

In substep e3), the values of the bottom hole flowing enthalpy BHFH n+ i,i, optionally the values of the bottom hole flowing temperature BHFT n+ i,i, and the updated pressure conditions P n+i of the reservoir 14 are used to calculate values of the bottom hole flowing pressure BHFP n+ i,i corresponding respectively to the flowrate potential values Qn+u-

Reading values of the bottom hole flowing temperature BHFT n+ i,i in the first set of data 40 is faster and more accurate. However, if values of the bottom hole flowing temperature BHFT n+ u are not obtained from the first set of data 40, they can be calculated knowing the fluid properties BHFH n+ u and BHFP n+ i .

For example, the values of the bottom hole flowing pressure BHFP n+ u are obtained by iterative convergence. If a BHFP n+ u value is selected during the convergence, then the BHFP n+ i,i value and the BHFH n+ u value allow obtaining a vapor/liquid fraction at the bottom hole 28. The vapor fraction and the BHFT n+ i value allow obtaining fluid properties, such as density and viscosity, that are used by the reservoir simulator 44 for calculating a pressure drop between the bottom hole 28 and the reservoir 14. If there is too much discrepancy between, on the one hand, the difference between the selected BHFP n+ u value and the updated pressure conditions P n+i and, on the other hand, the pressure drop calculated by the reservoir simulator 44, a modified BHFP n+ u value is tested until the discrepancy is below a predetermined level.

In step g), the surface network simulator 42 uses at least part of the first set of data 40 (in the example the VLP table 50) and the second set of data 48 (IPR table) generated in step e) in order to calculate the updated working point 46 of the well 20.

As already mentioned, in a particular embodiment, the updated working point 46 further comprises the bottom hole flowing pressure BHFP n+i for the next time step t n+ i.

The skilled person knows how many time steps to use and what length to give them, as a customary practice in time stepping methods, in order to obtain the well performance at a given time in the future.

Thanks to the above features, the process is able to determine a future performance of the well 20, by providing an injection performance obtained from or contained in the second set of data 48 (the IPR table). The injection performance provides a relationship between the bottom hole flowing pressure BHFP and the flowrate Q, or IPR, that works. This relationship takes into account the phases distribution of the fluid 12 at the bottom hole 28, whatever the flowrate value, which strongly impacts density and viscosity at a given (fixed) bottom hole flowing pressure BHFP. This allows accurately reflecting the injection performance of the well 20, which would not be the case if the phases distribution of the fluid 12 was not taken into account. Indeed, the phases distribution of the fluid 12 (liquid/dense, or only partly liquid, i.e. diphasic) completely changes the behavior of the fluid 12 through the perforations 30 of the well 20.

Ultimately, the process allows accurately controlling the well 20, particularly during phases where the fluid 12 is likely to be at least partly liquid, for example when the pressure in the reservoir 14 is still relatively low.

The correct phase distribution prediction, from the knowledge of the BHFH, allows also knowing the correct temperature of the fluid 12 being injected. This has a massive impact on the integrity of both the well 20 and the reservoir rock near the well. The well integrity could be at risk if the cement or any other parts were exposed to too cold temperatures for too long with a risk of losing well control or even fluid containment.

The rock integrity is of maximum importance too, since cooling the rocks around the well 20, together with the increase in pressure derived from fluid injection, may lead to the development of fracture, usually called thermally induced fractures (or TIF). These would dramatically improve the injectivity efficiency of the well 20, reducing the bottom hole flowing pressure BHFP for a given fixed flowrate. Correct TIF prediction is advantageous for the right planning of an injection project.

Also, knowing the injection temperature allows for the right estimates of temperature front developments in the reservoir rock. In the presence of water in the pore structure of the reservoir rock, this cooling could lead to hydrates formation. This advantageously allows predicting hydrates formation which may affect the performance of the well 20.