MAXIMIZE CONDENSATE RECOVERY IN GAS RESERVOIRS BY INJECTION OF VARIABLE FLUE GAS COMPOSITION

Abstract

A method to improve production of condensate is disclosed. The method includes obtaining a condensate fluids sample from a gas condensate reservoir, generating, from a laboratory pressure, volume and temperature (PVT) experiment of the condensate fluids sample, a liquid dropout curve, performing simulation of the laboratory PVT experiment based on Equations of State (EoS) of the condensate to generate a simulated liquid dropout curve, where the EoS is adjusted to match the simulated liquid dropout curve and the liquid dropout curve generated by the laboratory PVT experiment, performing, based on the adjusted EoS, a reservoir simulation of the gas condensate reservoir under injection of flue gas, where the reservoir simulation models a condensate banking phenomenon to generate an optimal flue gas ratio that maximizes a measure of condensate production, and facilitating, based on the optimal flue gas ratio, the production of the condensate in the gas condensate reservoir.

Description

BACKGROUND

Condensate is a low density and high API gravity (American Petroleum Institute gravity) hydrocarbon generally found in a gas reservoir. Gas reservoirs producing condensate in gas wells are referred to as gas condensate reservoirs. While the term “condensate” often refers to the liquid form of the low density and high API gravity hydrocarbon found in gas condensate reservoirs, the term “condensate” is broadened throughout this disclosure to describe all phases of such hydrocarbon in gas condensate reservoirs.

When reservoir pressure drops below the dew point during gas reservoir production, Condensate changes from gaseous phase to liquid phase (i.e., precipitates) in the reservoir around the well and rapidly accumulates as freshly produced gas continues to deposit additional liquid condensate near the well. The accumulation of liquid condensate near the well is referred to as the condensate banking phenomenon, which reduces the gas saturation and the gas well productivity.

Flue gas is the mixture of gases resulting from combustion and other reactions in a furnace, passing off through the smoke flue, and composed largely of nitrogen, carbon dioxide, carbon monoxide, water vapor, and often sulfur dioxide.

SUMMARY

In general, in one aspect, the invention relates to a method to improve production of condensate in a gas condensate reservoir. The method includes obtaining a condensate fluids sample from the gas condensate reservoir, generating, from a laboratory pressure, volume and temperature (PVT) experiment of the condensate fluids sample, a liquid dropout curve of the condensate fluids sample, performing simulation of the laboratory PVT experiment based on Equations of State (EoS) of the condensate to generate a simulated liquid dropout curve, wherein the EoS is adjusted to match the simulated liquid dropout curve and the liquid dropout curve generated by the laboratory PVT experiment, performing, based on the adjusted EoS, a reservoir simulation of the gas condensate reservoir under injection of flue gas, wherein the reservoir simulation models a condensate banking phenomenon to generate an optimal flue gas ratio that maximizes a measure of condensate production, and facilitating, based on the optimal flue gas ratio, the production of the condensate in the gas condensate reservoir.

In general, in one aspect, the invention relates to a reservoir simulator to improve production of condensate in a gas condensate reservoir. The reservoir simulator includes a computer processor, and memory storing instructions, when executed, causing the computer processor to perform, based on Equations of State (EoS) of the condensate, simulation of a laboratory pressure, volume and temperature (PVT) experiment of a condensate fluids sample obtained from the gas condensate reservoir to generate a simulated liquid dropout curve, wherein the EoS is adjusted to match the simulated liquid dropout curve and a liquid dropout curve generated by performing the laboratory PVT experiment, perform, based on the adjusted EoS, a reservoir simulation of the gas condensate reservoir under injection of flue gas, wherein the reservoir simulation models a condensate banking phenomenon to generate an optimal flue gas ratio that maximizes a measure of condensate production, and facilitate, based on the optimal flue gas ratio, the production of the condensate in the gas condensate reservoir.

In general, in one aspect, the invention relates to a system that includes a wellsite for production of condensate in a gas condensate reservoir, and a reservoir simulator comprising a computer processor and memory storing instructions, when executed, causing the computer processor to perform, based on Equations of State (EoS) of the condensate, simulation of a laboratory pressure, volume and temperature (PVT) experiment of a condensate fluids sample obtained from the gas condensate reservoir to generate a simulated liquid dropout curve, wherein the EoS is adjusted to match the simulated liquid dropout curve and a liquid dropout curve generated by performing the laboratory PVT experiment, perform, based on the adjusted EoS, a reservoir simulation of the gas condensate reservoir under injection of flue gas, wherein the reservoir simulation models a condensate banking phenomenon to generate an optimal flue gas ratio that maximizes a measure of condensate production, and facilitate, based on the optimal flue gas ratio, the production of the condensate in the gas condensate reservoir.

Other aspects and advantages of the claimed subject matter will be apparent from the following description and the appended claims.

BRIEF DESCRIPTION OF DRAWINGS

Specific embodiments of the disclosed technology will now be described in detail with reference to the accompanying figures. Like elements in the various figures are denoted by like reference numerals for consistency.

FIGS. 1A-1B show a system in accordance with one or more embodiments.

FIG. 2 shows a method flowchart in accordance with one or more embodiments.

FIGS. 3A-3C shows an example in accordance with one or more embodiments.

FIG. 4 shows a computing system in accordance with one or more embodiments.

DETAILED DESCRIPTION

In the following detailed description of embodiments of the disclosure, numerous specific details are set forth in order to provide a more thorough understanding of the disclosure. However, it will be apparent to one of ordinary skill in the art that the disclosure may be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the description.

Throughout the application, ordinal numbers (for example, first, second, third) may be used as an adjective for an element (that is, any noun in the application). The use of ordinal numbers is not to imply or create any particular ordering of the elements nor to limit any element to being only a single element unless expressly disclosed, such as using the terms “before”, “after”, “single”, and other such terminology. Rather, the use of ordinal numbers is to distinguish between the elements. By way of an example, a first element is distinct from a second element, and the first element may encompass more than one element and succeed (or precede) the second element in an ordering of elements.

In general, embodiments of the disclosure include systems and methods for improving recovery of condensate in a gas reservoir based on flue gas injection that modifies the reservoir fluid phase envelope. In one or more embodiments of the disclosure, flue gas is injected into a gas condensate reservoir to adjust the saturation or critical point location on a Pressure-Temperature (P-T) envelope in the reservoir to mitigate impact of condensate banking phenomena.

FIG. 1A shows a schematic diagram in accordance with one or more embodiments. More specifically, FIG. 1A illustrates a well environment (100) that includes a hydrocarbon reservoir (“reservoir”) (102) located in a subsurface hydrocarbon-bearing formation (“formation”) (104) and a well system (106). In one or more embodiments of the disclosure, the reservoir (102) is a gas reservoir to produce condensate, referred to as a gas condensate reservoir. The hydrocarbon-bearing formation (104) may include a porous or fractured rock formation that resides underground, beneath the earth's surface (“surface”) (108). In the case of the well system (106) being a hydrocarbon well, the reservoir (102) may include a portion of the hydrocarbon-bearing formation (104). The hydrocarbon-bearing formation (104) and the reservoir (102) may include different layers of rock having varying characteristics, such as varying degrees of permeability, porosity, capillary pressure, and resistivity. In the case of the well system (106) being operated as a production well, the well system (106) may facilitate the extraction of hydrocarbons (or “production”) from the reservoir (102).

In some embodiments, the well system (106) includes a wellbore (120), a well sub-surface system (122), a well surface system (124), and a well control system (“control system”) (126). The control system (126) may control various operations of the well system (106), such as well production operations, well completion operations, well maintenance operations, and reservoir monitoring, assessment and development operations. In some embodiments, the control system (126) includes a computer system that is the same as or similar to that of computer system (900) described below in FIG. 4 and the accompanying description.

The wellbore (120) may include a bored hole that extends from the surface (108) into a target zone of the hydrocarbon-bearing formation (104), such as the reservoir (102). An upper end of the wellbore (120), terminating at or near the surface (108), may be referred to as the “up-hole” end of the wellbore (120), and a lower end of the wellbore, terminating in the hydrocarbon-bearing formation (104), may be referred to as the “down-hole” end of the wellbore (120). The wellbore (120) may facilitate the circulation of drilling fluids during drilling operations, the flow of hydrocarbon production (“production”) (121) (e.g., oil and gas) from the reservoir (102) to the surface (108) during production operations, the injection of substances (e.g., water) into the hydrocarbon-bearing formation (104) or the reservoir (102) during injection operations, or the communication of monitoring devices (e.g., logging tools) into the hydrocarbon-bearing formation (104) or the reservoir (102) during monitoring operations (e.g., during in situ logging operations).

In some embodiments, during operation of the well system (106), the control system (126) collects and records wellhead data (140) for the well system (106). The wellhead data (140) may include, for example, a record of measurements of wellhead pressure (P_wh) (e.g., including flowing wellhead pressure), wellhead temperature (T_wh) (e.g., including flowing wellhead temperature), wellhead production rate (Q_wh) over some or all of the life of the well (106), and water cut data. In some embodiments, the measurements are recorded in real-time, and are available for review or use within seconds, minutes or hours of the condition being sensed (e.g., the measurements are available within 1 hour of the condition being sensed). In such an embodiment, the wellhead data (140) may be referred to as “real-time” wellhead data (140). Real-time wellhead data (140) may enable an operator of the well (106) to assess a relatively current state of the well system (106), and make real-time decisions regarding development of the well system (106) and the reservoir (102), such as on-demand adjustments in regulation of production flow from the well.

In some embodiments, the well sub-surface system (122) includes casing installed in the wellbore (120). For example, the wellbore (120) may have a cased portion and an uncased (or “open-hole”) portion. The cased portion may include a portion of the wellbore having casing (e.g., casing pipe and casing cement) disposed therein. The uncased portion may include a portion of the wellbore not having casing disposed therein. In some embodiments, the casing includes an annular casing that lines the wall of the wellbore (120) to define a central passage that provides a conduit for the transport of tools and substances through the wellbore (120). For example, the central passage may provide a conduit for lowering logging tools into the wellbore (120), a conduit for the flow of production (121) (e.g., oil and gas) from the reservoir (102) to the surface (108), or a conduit for the flow of injection substances (e.g., water) from the surface (108) into the hydrocarbon-bearing formation (104). In some embodiments, the well sub-surface system (122) includes production tubing installed in the wellbore (120). The production tubing may provide a conduit for the transport of tools and substances through the wellbore (120). The production tubing may, for example, be disposed inside casing. In such an embodiment, the production tubing may provide a conduit for some or all of the production (121) (e.g., oil and gas) passing through the wellbore (120) and the casing.

In some embodiments, the well surface system (124) includes a wellhead (130). The wellhead (130) may include a rigid structure installed at the “up-hole” end of the wellbore (120), at or near where the wellbore (120) terminates at the Earth's surface (108). The wellhead (130) may include structures for supporting (or “hanging”) casing and production tubing extending into the wellbore (120). Production (121) may flow through the wellhead (130), after exiting the wellbore (120) and the well sub-surface system (122), including, for example, the casing and the production tubing. In some embodiments, the well surface system (124) includes flow regulating devices that are operable to control the flow of substances into and out of the wellbore (120). For example, the well surface system (124) may include one or more production valves (132) that are operable to control the flow of production (121). For example, a production valve (132) may be fully opened to enable unrestricted flow of production (121) from the wellbore (120), the production valve (132) may be partially opened to partially restrict (or “throttle”) the flow of production (121) from the wellbore (120), and production valve (132) may be fully closed to fully restrict (or “block”) the flow of production (121) from the wellbore (120), and through the well surface system (124).

In some embodiments, the wellhead (130) includes a choke assembly. For example, the choke assembly may include hardware with functionality for opening and closing the fluid flow through pipes in the well system (106). Likewise, the choke assembly may include a pipe manifold that may lower the pressure of fluid traversing the wellhead. As such, the choke assembly may include set of high pressure valves and at least two chokes. These chokes may be fixed or adjustable or a mix of both. Redundancy may be provided so that if one choke has to be taken out of service, the flow can be directed through another choke. In some embodiments, pressure valves and chokes are communicatively coupled to the well control system (126). Accordingly, a well control system (126) may obtain wellhead data regarding the choke assembly as well as transmit one or more commands to components within the choke assembly in order to adjust one or more choke assembly parameters.

Keeping with FIG. 1A, in some embodiments, the well surface system (124) includes a surface sensing system (134). The surface sensing system (134) may include sensors for sensing characteristics of substances, including production (121), passing through or otherwise located in the well surface system (124). The characteristics may include, for example, pressure, temperature and flow rate of production (121) flowing through the wellhead (130), or other conduits of the well surface system (124), after exiting the wellbore (120).

In some embodiments, the surface sensing system (134) includes a surface pressure sensor (136) operable to sense the pressure of production (121) flowing through the well surface system (124), after it exits the wellbore (120). The surface pressure sensor (136) may include, for example, a wellhead pressure sensor that senses a pressure of production (121) flowing through or otherwise located in the wellhead (130). In some embodiments, the surface sensing system (134) includes a surface temperature sensor (138) operable to sense the temperature of production (121) flowing through the well surface system (124), after it exits the wellbore (120). The surface temperature sensor (138) may include, for example, a wellhead temperature sensor that senses a temperature of production (121) flowing through or otherwise located in the wellhead (130), referred to as “wellhead temperature” (T_wh). In some embodiments, the surface sensing system (134) includes a flow rate sensor (139) operable to sense the flow rate of production (121) flowing through the well surface system (124), after it exits the wellbore (120). The flow rate sensor (139) may include hardware that senses a flow rate of production (121) (Q_wh) passing through the wellhead (130).

In some embodiments, the well system (106) includes a reservoir simulator (160). For example, the reservoir simulator (160) may include hardware and/or software with functionality for generating one or more reservoir models regarding the hydrocarbon-bearing formation (104) and/or performing one or more reservoir simulations. For example, the reservoir simulator (160) may store well logs and data regarding reservoir samples for performing simulations. For example, the reservoir samples may include core samples and/or condensate fluids sample obtained from the reservoir. A reservoir simulator may further analyze the well log data, the reservoir sample data, seismic data, and/or other types of data to generate and/or update the one or more reservoir models. While the reservoir simulator (160) is shown at a well site, embodiments are contemplated where reservoir simulators are located away from well sites. In some embodiments, the reservoir simulator (160) may include a computer system that is similar to the computer system (900) described below with regard to FIG. 4 and the accompanying description.

FIG. 1B shows details of the reservoir simulator (160) depicted in FIG. 1A above in accordance with one or more embodiments disclosed herein. As shown in FIG. 1B, the reservoir simulator (160) has multiple components, including, for example, a buffer (114), an Equation of State (EoS) configuration engine (111), a simulation engine (112), and a pressure temperature (P-T) diagram analysis engine (113). Each of these components is discussed below.

In one or more embodiments, the buffer (114) may be implemented in hardware (i.e., circuitry), software, or any combination thereof. The buffer (114) is configured to store input data, output results, and intermediate data of the EoS configuration engine (111), the simulation engine (112), and the P-T diagram analysis engine (113). In one or more embodiments, the buffer (114) stores condensate composition (115), condensate liquid dropout curve (116), EoS (117), P-T diagrams (118), and flue gas ratio (119). The condensate composition (115) is a composition measure of the condensate obtained from a gas condensate reservoir. For example, the condensate composition (115) may indicate the type of condensate as lean, medium, or rich based on relative amount of heavier hydrocarbons versus lighter hydrocarbons in the condensate. For example, the molar percentage of C7+ in example lean, medium, and rich condensates may be 5.6%, 11.2%, and 14.8%, respectively. The condensate liquid dropout curve (116) describes the relationship of liquid phase volume percentage versus pressure of the condensate obtained from a gas condensate reservoir. The condensate liquid dropout curve (116) may be formatted as a data plot or in other data formats such as value pairs of volume percentage versus pressure. The EoS (117) is a thermodynamic equation relating states of the condensate under a given set of physical conditions, such as pressure, volume, temperature, or internal energy. For example, the EoS (117) may be based on Peng-Robinson Equation of State. The P-T diagrams (118) describe the phases of the condensate obtained from a gas condensate reservoir. The P-T diagrams (118) may be formatted as data plots or in other data formats such as pressure-temperature value pairs. In the P-T diagrams (118), the line that separates the solid and vapor phases is referred to the as sublimation line, the line that separates the solid and liquid phases is referred to the as the fusion line, and the line that separates the liquid and vapor phases is referred to as the vaporization line. The sublimation line, the fusion line, and the vaporization line collectively form the fluid envelope and the point where the three lines meet is referred to as the triple point. In other words, the triple point is the only point where all three phases can exist in equilibrium. The point where the vaporization line ends is referred to as the critical point. The critical point is also referred to as the saturation point as the point is where the saturated liquid and saturated vapor lines meet. Past this point, it is impossible for a liquid/vapor transformation to occur. The flue gas ratio (119) is the volume ratio between components of the flue gas, such as nitrogen, carbon dioxide, carbon monoxide, water vapor, sulfur dioxide, etc.

In one or more embodiments, the EoS configuration engine (111) may be implemented in hardware (i.e., circuitry), software, or any combination thereof. In one or more embodiments, a condensate fluids sample (e.g., having the condensate composition (115)) is obtained from the gas condensate reservoir for a laboratory pressure, volume and temperature (PVT) experiment. The EoS configuration engine (111) is configured to perform simulation of the laboratory PVT experiment based on Equations of State (EoS) (117) of the condensate to generate a simulated liquid dropout curve. By iteratively performing the simulation, the EoS (117) is adjusted to match the simulated liquid dropout curve and the liquid dropout curve (116) generated by physically performing the laboratory PVT experiment.

In one or more embodiments, the simulation engine (112) may be implemented in hardware (i.e., circuitry), software, or any combination thereof. In particular, the simulation engine (112) is configured to perform a reservoir simulation of the gas condensate reservoir under injection of flue gas. The reservoir simulation is performed based on the adjusted EoS (117) to model the condensate banking phenomena.

In one or more embodiments, the P-T diagram analysis engine (113) may be implemented in hardware (i.e., circuitry), software, or any combination thereof. In particular, the P-T diagram analysis engine (113) is configured to analyze P-T diagrams (118) generated based on the results of the reservoir simulation to determine an optimal value of the flue gas ratio (119) for improving the condensate production.

In one or more embodiments, the EoS configuration engine (111), the simulation engine (112), and the P-T diagram analysis engine (113) collectively perform the functionalities described above using the method described in reference to FIG. 2 below.

Although the reservoir simulator (160) is shown as having four components (111, 112, 113, 114), in other embodiments, the reservoir simulator (160) may have more or fewer components. Further, the functionality of each component described above may be split across multiple components. Further still, each component (111, 112, 113, 114) may be utilized multiple times to carry out an iterative operation.

FIG. 2 shows a flowchart in accordance with one or more embodiments disclosed herein. One or more of the steps in FIG. 2 may be performed by the components of the well environment (100) and the reservoir simulator (160), discussed above in reference to FIGS. 1A-1B. In one or more embodiments, one or more of the steps shown in FIG. 2 may be omitted, repeated, and/or performed in a different order than the order shown in FIG. 2. Accordingly, the scope of the disclosure should not be considered limited to the specific arrangement of steps shown in FIG. 2.

Referring to FIG. 2, initially in Step 200, laboratory pressure, volume and temperature (PVT) experiments are performed using a condensate fluids sample obtained from a gas condensate reservoir. Each PVT experiment mimics a form of phase behavior progression during production of the condensate fluids from the gas condensate reservoir to the surface facilities during the gas condensate reservoir production. For example, the PVT experiments may include a constant volume depletion (CVD) test that generates, among others, a liquid dropout curve and a composition measure of the condensate fluids sample.

Based on the composition measure of the condensate fluids sample, the Equations of state (EoS) is configured to simulate the PVT experiments and generate a simulated liquid dropout curve. The EoS is iteratively adjusted (i.e., tuned) to match the simulated liquid dropout curve and the liquid dropout curve generated by the PVT experiments. In one or more embodiments, the critical pressure, critical temperature, and acentric factor are the parameters used to tuned the Equation of State.

In Step 201, a reservoir simulation is performed to model the condensate banking phenomena of the gas condensate reservoir. Specifically, the reservoir simulation is performed based on the EoS configured in Step 200 above to generate pressure-temperature data of the condensate fluids and/or a mixture of condensate fluids and injected flue gas with varying flue gas ratio. In particular, the simulation models the flue gas injection and considers flue gas flow rate and pressure in addition to the flue gas ratio. In one or more embodiments, the simulation is performed multiple times, referred to as simulation scenarios, for each of a set of selected flue gas ratios to generate a corresponding measure of condensate production. The range of selected flue gas ratio depends on the gas composition and simulation scenarios to identify the ratios needed to maximize condensate recovery.

In Step 202, the simulated pressure-temperature data is analyzed to identify an optimal ratio of flue gases (referred to as the optimal flue gas ratio) based on different simulation scenarios to maximize the measure of condensate production. For example, the measure of condensate production may correspond to the production flow rate of the condensate. The optimal flue gas ratio is the volume ratio between carbon dioxide, nitrogen, and oxygen in the flue gas that maximizes the production flow rate of the condensate.

In one or more embodiments, the simulated pressure-temperature data is plotted as P-T diagrams for analysis. Including the flue gas with the optimal flue gas ratio in the condensate adjusts the critical or saturation point in the P-T diagrams such that early precipitation of condensate in the condensate banking phenomena is delayed to improve the condensate recovery.

In Step 203, the proper case is identified that will assist in maximizing the recovery factor. In one or more embodiments, the proper case is based on a cumulative gas condensate production, i.e., cumulated production flow rate of the condensate.

In Step 204, the flue gas with the optimal flue gas ratio is injected into the gas condensate reservoir to improve recovery of condensate production in the gas condensate reservoir. In one or more embodiments, the flue gas is injected into the gas condensate reservoir through the production wellbore. In alternative embodiments, the flue gas is injected into the gas condensate reservoir through an injection well adjacent to the production wellbore. In one or more embodiments, the flue gas is produced in a furnace at the wellsite and directed to the wellbore through the smoke flue and connecting pipes.

FIGS. 3A-3C shows an implementation example in accordance with one or more embodiments. Gas condensate reservoirs have a significant share of the world's gas supply. Recovered condensate of these reservoirs has a high value in the market. However, when the reservoir pressure declines below the dew point pressure, liquid may drop out of gas condensate inside the reservoir and may leave a significant part of the condensate irrecoverable. In particular, the recovery factor for rich gas condensate reservoirs is very low due to severe condensate banking phenomena. The implementation example shown in FIGS. 3A-3C is based on the system and method flowchart described in reference to FIGS. 1A, 1B, and 2 above that modify the reservoir fluid phase envelop by flue gas injection to improve the recovery of condensate and realize the economic value of the gas field.

Specifically, FIGS. 3A-3C shows an example of a P-T diagram (301) of the unmodified condensate in the gas reservoir, a P-T diagram (302) of the condensate with injected carbon dioxide in the gas reservoir, and a P-T diagram (303) of the condensate with injected flue gas of the optimal flue gas ratio in the gas reservoir. The critical points in the P-T diagrams (301, 302, 303) are marked by “X”. The critical point in the P-T envelope of the P-T diagram (303) is adjusted from those of the P-T diagram (301) and P-T diagram (302) to optimally delaying the early precipitation of condensate and improving gas recovery. After injection of the flue gases, the flue gases react with formation fluid and change its composition and properties, which results in lowering the dew point pressure thereby postponing the condensate banking phenomena. For example, the dew point of the unmodified condensate in the gas reservoir is at 2700 psi and 170° F., while the dew point pressure is reduced to 2550 psi with injected flue gas of the optimal flue gas ratio in the gas reservoir.

Embodiments disclosed herein may be implemented on virtually any type of computing system, regardless of the platform being used. For example, the computing system may be one or more mobile devices (e.g., laptop computer, smart phone, personal digital assistant, tablet computer, or other mobile device), desktop computers, servers, blades in a server chassis, or any other type of computing device or devices that includes at least the minimum processing power, memory, and input and output device(s) to perform one or more embodiments. For example, as shown in FIG. 4, the computing system (400) may include one or more computer processor(s) (402), associated memory (404) (e.g., random access memory (RAM), cache memory, flash memory, etc.), one or more storage device(s) (406) (e.g., a hard disk, an optical drive such as a compact disk (CD) drive or digital versatile disk (DVD) drive, a flash memory stick, etc.), and numerous other elements and functionalities. The computer processor(s) (402) may be an integrated circuit for processing instructions. For example, the computer processor(s) may be one or more cores, or micro-cores of a processor. The computing system (400) may also include one or more input device(s) (410), such as a touchscreen, keyboard, mouse, microphone, touchpad, electronic pen, or any other type of input device. Further, the computing system (400) may include one or more output device(s) (408), such as a screen (e.g., a liquid crystal display (LCD), a plasma display, touchscreen, cathode ray tube (CRT) monitor, projector, or other display device), a printer, external storage, or any other output device. One or more of the output device(s) may be the same or different from the input device(s). The computing system (400) may be connected to a network (412) (e.g., a local area network (LAN), a wide area network (WAN) such as the Internet, mobile network, or any other type of network) via a network interface connection (not shown). The input and output device(s) may be locally or remotely (e.g., via the network (412)) connected to the computer processor(s) (402), memory (404), and storage device(s) (406). Many different types of computing systems exist, and the aforementioned input and output device(s) may take other forms.

Software instructions in the form of computer readable program code to perform embodiments of the disclosure may be stored, in whole or in part, temporarily or permanently, on a non-transitory computer readable medium such as a CD, DVD, storage device, a diskette, a tape, flash memory, physical memory, or any other computer readable storage medium. Specifically, the software instructions may correspond to computer readable program code that when executed by a processor(s), is configured to perform embodiments disclosed herein.

Further, one or more elements of the aforementioned computing system (400) may be located at a remote location and be connected to the other elements over a network (412). Further, one or more embodiments may be implemented on a distributed system having a plurality of nodes, where each portion of the disclosure may be located on a different node within the distributed system. In one embodiment, the node corresponds to a distinct computing device. Alternatively, the node may correspond to a computer processor with associated physical memory. The node may alternatively correspond to a computer processor or micro-core of a computer processor with shared memory and/or resources.

While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this disclosure, will appreciate that other embodiments can be devised which do not depart from the scope of the disclosure as disclosed herein. Accordingly, the scope of the disclosure should be limited only by the attached claims.

Claims

1. A method to improve production of condensate in a gas condensate reservoir, comprising:

obtaining a condensate fluids sample from the gas condensate reservoir;

generating, from a laboratory pressure, volume and temperature (PVT) experiment of the condensate fluids sample, a liquid dropout curve of the condensate fluids sample;

performing simulation of the laboratory PVT experiment based on Equations of State (EoS) of the condensate to generate a simulated liquid dropout curve, wherein the EoS is adjusted to match the simulated liquid dropout curve and the liquid dropout curve generated by the laboratory PVT experiment;

performing, based on the adjusted EoS, a reservoir simulation of the gas condensate reservoir under injection of flue gas, wherein the reservoir simulation models a condensate banking phenomenon to generate an optimal flue gas ratio that maximizes a measure of condensate production; and

facilitating, based on the optimal flue gas ratio, the production of the condensate in the gas condensate reservoir.

2. The method of claim 1, further comprising:

further generating, from the laboratory PVT experiment of the condensate fluids sample, a composition measure of the condensate fluids sample; and

configuring, based on the composition measure, the EoS for simulating the PVT experiment.

3. The method of claim 2,

wherein the composition measure identifies the condensate fluids sample as one of a lean composition type, a medium composition type, and a rich composition type.

4. The method of claim 1, further comprising:

generating, based on simulated pressure-temperature (P-T) data from the reservoir simulation of the gas condensate reservoir under injection of flue gas, a plurality of P-T diagrams corresponding to a plurality of flue gas ratios; and

analyzing the plurality of the P-T diagrams to select an optimal P-T diagram where a critical point is optimally adjusted to delay early precipitation of condensate in the condensate banking phenomenon,

wherein the optimal P-T diagram corresponds to the optimal flue gas ratio.

5. The method of claim 1, further comprising:

injecting, into the gas condensate reservoir during production of the condensate, the flue gas based on the optimal flue gas ratio.

6. The method of claim 5,

wherein the flue gas is injected via a production wellbore of the gas condensate reservoir during the production of the condensate.

7. The method of claim 5,

wherein the flue gas is injected via an injection well in a vicinity of the production wellbore.

8. The method of claim 5,

wherein the flue gas is produced from combustion in a furnace at a wellsite of the gas condensate reservoir.

9. A reservoir simulator to improve production of condensate in a gas condensate reservoir, comprising:

a computer processor; and

memory storing instructions, when executed, causing the computer processor to: perform, based on Equations of State (EoS) of the condensate, simulation of a laboratory pressure, volume and temperature (PVT) experiment of a condensate fluids sample obtained from the gas condensate reservoir to generate a simulated liquid dropout curve, wherein the EoS is adjusted to match the simulated liquid dropout curve and a liquid dropout curve generated by performing the laboratory PVT experiment; perform, based on the adjusted EoS, a reservoir simulation of the gas condensate reservoir under injection of flue gas, wherein the reservoir simulation models a condensate banking phenomenon to generate an optimal flue gas ratio that maximizes a measure of condensate production; and facilitate, based on the optimal flue gas ratio, the production of the condensate in the gas condensate reservoir.

10. The reservoir simulator of claim 9, the instructions, when executed, further causing the computer processor to:

further generate, from the laboratory PVT experiment of the condensate fluids sample, a composition measure of the condensate fluids sample; and

configure, based on the composition measure, the EoS for simulating the PVT experiment.

11. The reservoir simulator of claim 10,

wherein the composition measure identifies the condensate fluids sample as one of a lean composition type, a medium composition type, and a rich composition type.

12. The reservoir simulator of claim 9, the instructions, when executed, further causing the computer processor to:

generate, based on simulated pressure-temperature (P-T) data from the reservoir simulation of the gas condensate reservoir under injection of flue gas, a plurality of P-T diagrams corresponding to a plurality of flue gas ratios; and

analyze the plurality of the P-T diagrams to select an optimal P-T diagram where a critical point is optimally adjusted to delay early precipitation of condensate in the condensate banking phenomenon,

wherein the optimal P-T diagram corresponds to the optimal flue gas ratio.

13. The reservoir simulator of claim 9,

wherein the flue gas is injected into the gas condensate reservoir during the production of the condensate based on the optimal flue gas ratio.

14. The reservoir simulator of claim 13,

wherein the flue gas is injected via a production wellbore of the gas condensate reservoir or an injection well in a vicinity of the production wellbore, and

wherein the flue gas is produced from combustion in a furnace at a wellsite of the gas condensate reservoir.

15. A system comprising:

a wellsite for production of condensate in a gas condensate reservoir; and

a reservoir simulator comprising a computer processor and memory storing instructions, when executed, causing the computer processor to: perform, based on Equations of State (EoS) of the condensate, simulation of a laboratory pressure, volume and temperature (PVT) experiment of a condensate fluids sample obtained from the gas condensate reservoir to generate a simulated liquid dropout curve, wherein the EoS is adjusted to match the simulated liquid dropout curve and a liquid dropout curve generated by performing the laboratory PVT experiment; perform, based on the adjusted EoS, a reservoir simulation of the gas condensate reservoir under injection of flue gas, wherein the reservoir simulation models a condensate banking phenomenon to generate an optimal flue gas ratio that maximizes a measure of condensate production; and facilitate, based on the optimal flue gas ratio, the production of the condensate in the gas condensate reservoir.

16. The system of claim 15, the instructions, when executed, further causing the computer processor to:

further generate, from the laboratory PVT experiment of the condensate fluids sample, a composition measure of the condensate fluids sample; and

configure, based on the composition measure, the EoS for simulating the PVT experiment.

17. The system of claim 16,

wherein the composition measure identifies the condensate fluids sample as one of a lean composition type, a medium composition type, and a rich composition type.

18. The system of claim 15, the instructions, when executed, further causing the computer processor to:

generate, based on simulated pressure-temperature (P-T) data from the reservoir simulation of the gas condensate reservoir under injection of flue gas, a plurality of P-T diagrams corresponding to a plurality of flue gas ratios; and

analyze the plurality of the P-T diagrams to select an optimal P-T diagram where a critical point is optimally adjusted to delay early precipitation of condensate in the condensate banking phenomenon,

wherein the optimal P-T diagram corresponds to the optimal flue gas ratio.

19. The system of claim 15,

wherein the flue gas is injected into the gas condensate reservoir during the production of the condensate based on the optimal flue gas ratio.

20. The system of claim 15,

wherein the flue gas is injected via a production wellbore of the gas condensate reservoir or an injection well in a vicinity of the production wellbore, and

wherein the flue gas is produced from combustion in a furnace at the wellsite of the gas condensate reservoir.