Producing Hydrocarbons from a Subsurface Reservoir

This application claims the benefit of priority to U.S. Patent Application No. 63/637,571, filed on Apr. 23, 2024, the contents of which are incorporated by reference herein.

This specification generally relates to producing hydrocarbons from a subsurface reservoir, particularly using injection wells as part of the production process.

Primary recovery methods typically only extract about 30% of oil initially present in a reservoir. In some situations, water injection or water flooding is a secondary hydrocarbon recovery technique employed before enhanced oil recovery technologies are deployed. In water injection, water is injected into a subsurface formation under high pressure and temperature conditions to extract more oil after the primary recovery phase. The injected water can maintain pressure in the reservoir and/or drive oil towards production wells. Sources of water for water injection include produced water, seawater, and aquifer water from water-bearing formations outside the oil reservoir.

This specification describes an approach to producing hydrocarbons from a subsurface reservoir using injection wells as part of the production process. This approach can improve the efficiency of water injection operations for oilfields that are being pressurized at multiple locations. An injection control engine includes a reservoir model and an allocation module. Initial injection targets are set based on simulations run on the reservoir model that set injection volumes per injection location to sufficiently pressurize the reservoir to achieve desired production levels. The targets represent an injection schedule with daily rates for the upcoming scheduling horizon (e.g. 1 month). The allocation module is then used to allocate each injection volume to an injection plant. The model also performs other tasks such as varying the initial injection targets within pre-set limits. This enables reductions in the overall energy consumption by reducing the number of operating pumps and/or allocating injection to more efficient pumps. The adjusted injection targets are validated against reservoir simulations and are then used as final targets for the reservoir.

The approach disclosed in this specification can provide one or more of the following advantages. This approach can be used to schedule and allocate water injection to improve the efficiency of water injection operations for oilfields that are being pressurized at multiple locations. In particular, this approach can reduce energy consumption in surface equipment associated with water injection, which is an element in approaches to decarbonize water injection facilities. In addition, significant benefits can be attained through providing a schedule, in which injection is potentially ramped up for part of the month then reduced for the remainder of the month. This approach also imposes user specified constraints for maximum days of no injection or variations from initial targets which increase the usability of this approach for field applications.

This approach can also facilitate scheduling maintenance windows to service the injection pumps by efficiently allocating the production to other injection plants. The schedule provided also reduces fluctuations in the injection and pumping rates. This provides better controllability particularly since some wells are at remote locations and adjusting their injection rate frequently is difficult.

The details of one or more embodiments of these systems and methods are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of these systems and methods will be apparent from the description and drawings, and from the claims.

Like reference symbols in the various drawings indicate like elements.

This specification describes an approach to producing hydrocarbons from a subsurface reservoir using injection wells as part of the production process. This approach can improve the efficiency of water injection operations for oilfields that are being pressurized at multiple locations. An injection control engine includes a reservoir model and an allocation module. Initial injection targets are set based on simulations run on the reservoir model that set injection volumes per injection location to sufficiently pressurize the reservoir to achieve desired production levels. The targets represent an injection schedule with daily rates for the upcoming scheduling horizon (e.g. 1 month). The allocation module is then used to allocate each injection volume to an injection plant. The model also performs other tasks such as varying the initial injection targets within pre-set limits. This enables reductions in the overall energy consumption by reducing the number of operating pumps and/or allocating injection to more efficient pumps. The adjusted injection targets are validated against reservoir simulations and are then used as final targets for the reservoir.

is a schematic view illustrating hydrocarbon exploration and production activities in a subsurface formation. The production activities include injecting water into the subsurface formation to maintain pressure in the subsurface formation.

The subsurface formationincludes a layer of impermeable cap rocksat the surface. Facies underlying the impermeable cap rocksinclude layers,, and. A fault lineextends across the layerand the layer.

Oil and gas tend to rise through permeable reservoir rock until further upward migration is blocked, for example, by the layer of impermeable cap rock. Seismic surveys attempt to identify locations where interaction between layers of the subsurface formationare likely to trap oil and gas by limiting this upward migration. For example,shows an anticline trap, where the layer of impermeable cap rockhas an upward convex configuration, and a fault trap, where the fault linemight allow oil and gas to flow in with clay material between the walls traps the petroleum. Other traps include salt domes and stratigraphic traps.

A systemic survey is illustrated with a seismic source(for example, a seismic vibrator or an explosion) generating seismic waves that propagate in the earth. Although illustrated as a single component in, the source or sourcesare typically a line or an array of sources. The generated seismic waves include seismic body wavesthat travel into the ground and seismic surface wavestravel along the ground surface and diminish as they get further from the surface. As the seismic wavescontact interfaces between geologic bodies or layers that have different velocities, the interface reflects some of the energy of the seismic wave and refracts part of the energy of the seismic wave. Such interfaces are sometimes referred to as horizons.

The seismic body wavesare received by a sensor or sensors. Although illustrated as a single component in, the sensor or sensorsare typically a line or an array of sensorsthat generate an output signal in response to received seismic waves including waves reflected by the horizons in the subsurface formation. The sensorscan be geophone-receivers that produce electrical output signals transmitted as input data, for example, to a computeron a seismic control truck. Based on the input data, the computermay generate a seismic data output such as, for example, a seismic two-way response time plot.

The seismic surface wavestravel more slowly than seismic body waves. Analysis of the time it takes seismic surface wavesto travel from source to sensor can provide information about near surface features.

In some embodiments, a wellborethat has been drilled in the subsurface formationis logged in a well logging operation. The wellboreextends downhole from a wellhead. The wellboreis a vertical wellbore but well logging can also be performed in other wellbores, for example, slanted or horizontal wellbores. In the well logging operation, the wellborepenetrates through three layers,, andof a subsurface formation. A control trucklowers a logging tooldown the wellboreon a wireline.

The logging toolis string of one or more instruments with sensors operable to measure geophysical properties of the subsurface formation. For example, logging tools can include resistivity logs, borehole image logs, porosity logs, density logs, or sonic logs.

As the logging tooltravels downhole, measurements of formations properties are recorded to generate a well log. In the illustrated operation, the data are recorded at the control truckin real-time. Real-time data are recorded directly against measured cable depth. In some well-logging operations, the data is recorded at the logging tooland downloaded later. In this approach, the downhole data and depth data are both recorded against time. The two data sets are then merged using the common time base to create an instrument response versus depth log.

In the well logging operation, the well logging is performed on a wellborethat has already been drilled. In some operations, well logging is performed in the form of logging while drilling techniques. In these techniques, the sensors are integrated into the drill string and the measurements are made in real-time, during drilling rather than using sensors lowered into a well after drilling.

A control centercan be operatively coupled to the seismic control truckand other data acquisition and wellsite systems. The control centermay have computer facilities for receiving, storing, processing, and analyzing data from the seismic control truckand other data acquisition and wellsite systems that provide additional information about the subsurface formation. For example, the control centercan receive data from a computerassociated with a well logging unit.

The computer systemscan be located in a different location than the control center. Some computer systems are provided with functionality for manipulating and analyzing the data, such as performing seismic interpretation or borehole resistivity image log interpretation to identify geological surfaces in the subsurface formation or performing simulation, planning, and optimization of production operations of the wellsite systems.

The computer systemscan be configured to analyze, model, control, optimize, or perform management tasks of field operations associated with development and production of resources such as oil and gas from the subsurface formation. For example, an injection welland a production wellextend into layerof the subsurface formation. A water injection plantconnected to the injection wellby conduits is used to inject water into the subsurface formation. Although illustrated as single components in, typically fields will include multiple injection wells, multiple production wells, and multiple water injection plants.

Based on data gathered by the exploratory field operations, the computer systemscan generate models such as a reservoir model for portions of the subsurface formation. These models can simulate the effects of production field operations (e.g., injecting water or carbon dioxide through the injection wellto increase the production of hydrocarbons through the production well). The simulations can be used to plan and, in some instances, control field operations (e.g., the operation of pumps associated with the injection welland the production well). For example, in the illustrated oilfield, the computer systemsare configured to implement the previously described injection control engine to generate an injection schedule with daily rates for the upcoming scheduling horizon (e.g. 1 month). After validation, the injection schedule is used to control the multiple injection wells, the multiple production wells, and the multiple water injection plantsand distribute injection volumes between them.

In some embodiments, results generated by the computer systemsmay be displayed for user viewing using local or remote monitors or other display units. One approach to analyzing seismic data is to associate the data with portions of a seismic cube representing the subsurface formation. The seismic cube can also display results of the analysis of the seismic data associated with the seismic survey.

illustrates an oilfield with a water injection network with seven injection wells, four production wells, and three water injection plants,Water entering the water injection network typically undergoes preliminary treatment at one or more treatment facilities (not shown). The specific treatment(s) required depend on the source of the water being used for injection. For example, produced water, seawater, and aquifer water will require different preliminary treatment before injection.

Each water injection plantis equipped with a set of motor or gas turbine driven pumps. The pumps have varying minimum and maximum capacities and efficiencies. The water injection plantreceives water from the preliminary treatment facilities. The water injection plantpressurizes the water for transfer to the other water injection plantsand also injects the water into the subsurface formation through three injection wellslocated along an eastern flank of the reservoir from which oil is being produced. The term “flank” can be used to refer to a collection of injection wells strategically positioned around the edges of the main reservoir to maintain pressure and enhance oil recovery. The water injection plantreceives water from the water injection plantand injects the water into the subsurface formation through two injection wellslocated along a northern flank of the reservoir. The water injection plantreceives water from the water injection plantand injects the water into the subsurface formation through two injection wellslocated along a western flank of the reservoir.

Isobars onillustrate pressure gradients in the reservoir. Injection of water into the reservoir through the injection wellsincreases pressure in the reservoir around the production wells.

is a schematic illustrating an example systemused to implement processes for controlling water injection into a reservoir. The systemincludes an injection control enginewith a reservoir modeland an allocation module.

The reservoir modelis used to simulate the behavior of the oil reservoir over time. It starts with a detailed characterization of the reservoir, including geological properties, fluid properties and well configurations and their placement. The model simulates how fluids (oil, water, gas) move within the reservoir. The reservoir modelcan be used to set water injection targets to maintain pressure given recovery targets. The reservoir modelcan be used to set how much water needs to be injected to maintain adequate pressure which facilitates the movement of oil towards production wells. The model can be used to forecast oil production over time. This allows adjusting injection targets to meet production targets. Initial injection targets are set based on simulations run on the reservoir modelthat set injection volumes per injection location to sufficiently pressurize the reservoir to achieve desired production levels. The targets represent an injection schedule with daily rates for the upcoming scheduling horizon (e.g. 1 month).

The allocation moduleis then used to allocate each injection volume to an injection plant. The model also performs other tasks such as varying the initial injection targets within pre-set limits. This enables reductions in the overall energy consumption by reducing the number of operating pumps and/or allocating injection to more efficient pumps. The adjusted injection targets are validated against reservoir simulations and are then used as final targets for the reservoir.

In the prototype system, the allocation moduleused Mixed Integer Linear (or Nonlinear) Programming (MILP/MINLP) to control pumps associated with the injection wellsand the water injection plantsto minimize the overall energy consumption of the network. The allocation module is configured to allow users to implement constraints reflecting the configuration of the injection wellsand the water injection plantsin the water injection network. This approach results in a schedule with limited changes in the pumping and injection rates through the month. The usability of the models and the applicability of the results is increased by avoiding frequent adjustments of the injection flowrate for each well or flank. It is also possible to shutdown injection for a given maximum number of days. It is also mandatory to meet month end total targets within a given compliance limit, which can be separately specified for each flank.

For example, the prototype systemdefined nine constraints. Constraints 1 and 2 control the total supply of each water injection plant falls between the aggregated minimum and maximum limits of operating pumps for that specific plant. Constraints 3 and 4 limited the total injection to each flank between the minimum and maximum allowed rates. Constraint 5 set the injection to a given flank to 0 when there is user-defined shutdown event at a given period t. Constraint 6 balances the supply from each water injection plant with the rate from its pumps. Constraint 7 limits the number of shutdown days to those defined by the user. Constraint 8 requires the model meet the month end injection target within a user-defined minimum compliance. Constraint 9 requires the water supplied by a given plant is equal the water rate of the connected receiving plants.

The allocation module includes an optimization model configured with an objective function which controls water injection at oil and gas fields to minimize the overall power consumption of the water injection operation while complying with operational constraints. A prototype of the system implemented with the objective function represented by Eq. 1.

in which sets t, p and f refer to time periods, WIPs and flanks, respectively. Variables x, y and z refer to continuous, binary and integer variables, respectively. The first term in Eq. (1) calculates the total cost of used pumps at each WIP, where zis the number of running pumps at the WIP and Costis the cost of using a pump, which is assumed to be the same for all pumps at the same WIP to reduce the problem size. The second term penalizes the model for setting zero injection rate at a given day to avoid unnecessary shut down of injection, where yis a binary variable which is activated when there is zero injection. The third and fourth terms minimize fluctuations in injection and pumping rates, respectively, where xis a variable that is constrained to equal or exceed daily variations in injection rates and xis defined to equal or exceed daily variations in pumping rates as will be illustrated in the constraints.

Mathematically speaking, the objective function minimizes the summation of four terms. The first term calculates the total cost of used pumps at each water injection plant. The second term penalizes the model for setting zero injection rate at a given day to avoid unnecessary shut down of injection. The third and fourth terms minimize fluctuations in injection and pumping rates, respectively. The optimization problem is then solved to the optimum values of all the variables. The pump rates are then assigned to each pump's control logic through a distributed control system. The injection rates are then applied by throttling the control valves at each injection well. Each water injection plant is connected to a set of flanks. The wells can be modeled explicitly or their assigned production targets can be grouped into their respective flanks.

is a flow chart illustrating a methodof producing hydrocarbons from a subsurface reservoir using injection wells. The methodcan include receiving reservoir parameters, initial pressures, and target pressures (step). In some implementations, the method uses a previously implemented reservoir model which already incorporates reservoir parameters, initial pressures, and target pressures.

The reservoir model incorporating reservoir parameters and initial pressures is run to identify initial injection targets to achieve target pressures (step). Based on initial injection targets, an injection schedule that minimizes the overall power consumption of pumps associated with the plurality of injection wells is developed using an allocation module incorporating operational constraints of the pumps (step). The allocation module can be implemented with mixed integer programming.

Typically, each well of the plurality of injection wells is associated with a water injection plant and the allocation module is configured to incorporate constraints reflecting the configuration of the plurality of injection wells and the water injection plants. In some cases, the constraints control a total supply of each water injection plant to fall between the aggregated minimum and maximum limits of operating pumps for that specific water injection plant. In some cases, the constraints limit total injection to each flank of the reservoir to between minimum and maximum allowed rates. In some cases, the constraints balance supply from each water injection plant with the rate from its pumps. In some cases, the constraints require the water supplied by a water injection plant is equal the water rate of connected receiving water injection plant.

The injection schedule can include daily injection rates for the plurality of wells for an upcoming scheduling horizon (e.g., a month). In some applications, the injection schedule includes a daily injection rate for each well of the plurality of injection wells. In some applications, the injection schedule includes a daily injection rate for groups of wells of the plurality of injection wells.

After the injection schedule is developed and verified, the pumps are controlled to implement the injection schedule (step). Hydrocarbons can be produced through production wells associated with the plurality of injection wells (step) contemporaneously with injection of water through the injection wells.

illustrates an oilfield to which a prototype system was applied to generate the daily scheduling of a water injection networkin the Ghawar oilfield. This network comprises a multitude of nodes, where seawater first undergoes a series of preliminary treatments. The treated seawater is then pumped through an extensive network of plants, which either further pressurize the water for transfer to other plants or directly inject it underground through remote wells, which are located along piping flanks.

The starting point of the water injection networkis the Qurayyah Seawater Plant, located on the Arabian Gulf. The facility is capable of processing somemillion barrels of seawater daily. The treated water leaves Qurayyah south bound to the ‘Uthmaniyah Water Supply Plant (UWSP)and north to the A in Dar Water Injection Plant (ADWIP). From UWSP, water is pumped to a network of water injection plants (WIPs). Each WIPdirects water to a number of remote injection wells located along flanks.

Four ‘Uthmaniyah WIPssustain pressure in the Ghawar's North section, while the Hawiyah WIP(HAWIP) injects to wells that are connected directly to it and additional ones further south at HRDH. In the North, water is pumped to the Sulfate Removal Facility(SRF) and ADWIP. At ADWIP water is directed to remote injection wells and is also sent to Khurais Central Processing Facility(KhCPF), which is responsible for injecting water at the Khurais field.

Each WIPis equipped with a set of motor or gas turbine driven pumps with varying minimum and maximum capacities as presented in Table 1. Each WIPis connected to a set of flanks. In the test application, wells were not modelled explicitly. Rather their assigned production targets were grouped into their respective flanks. Two flanks are shared between UWIP-and UWIP-. One Flank is shared between UWIP-and HAWIP and one flank is shared between UWIP-and HA WIP. The constraints of this application provided a model which minimizes the overall energy consumption of the network while providing a schedule with minimal disruptions both in the pumping and injection rates. This implementation allowed for injection to be shutdown for a given maximum number of days. If not shutdown, each flank is constrained to operate between given minimum and maximum rates while meeting month end total targets within a given compliance limit, which can be separately specified for each flank. This implementation assumes that if pumps are used, a fixed base cost is incurred. The fixed base cost varies per pump, but is not a function of the flowrate.

Running the prototype system provided a schedule with daily injection rates at each flank, efficient pump operational parameters, and supply strategies for swing flanks. The model accommodates user-defined constraints, ensuring month-end compliance targets are met. By introducing penalty terms in the objective function, the model minimizes daily operational variations, producing a practical and operationally acceptable schedule.

Employing techniques to enhance computational efficiency, the model reduces CPU times from hours for reservoir model-based approaches to an average ofseconds. The schedule provided by running the prototype system reduced energy consumption for the water injection network by up to 7% compared to the current schedule.

illustrates hydrocarbon production operationsthat include both one or more field operationsand one or more computational operations, which exchange information and control exploration for the production of hydrocarbons. In some implementations, outputs of techniques of the present disclosure can be performed before, during, or in combination with the hydrocarbon production operations, specifically, for example, either as field operationsor computational operations, or both.

Examples of field operationsinclude forming/drilling a wellbore, hydraulic fracturing, producing through the wellbore, injecting fluids (such as water) through the wellbore, to name a few. In some implementations, methods of the present disclosure can trigger or control the field operations. For example, the methods of the present disclosure can generate data from hardware/software including sensors and physical data gathering equipment (e.g., seismic sensors, well logging tools, flow meters, and temperature and pressure sensors). The methods of the present disclosure can include transmitting the data from the hardware/software to the field operationsand responsively triggering the field operationsincluding, for example, generating plans and signals that provide feedback to and control physical components of the field operations. Alternatively or in addition, the field operationscan trigger the methods of the present disclosure. For example, implementing physical components (including, for example, hardware, such as sensors) deployed in the field operationscan generate plans and signals that can be provided as input or feedback (or both) to the methods of the present disclosure.