NO20140899A1 - Estimation of flow rates from multiple hydrocarbon reservoir layers into a production well - Google Patents

Abstract

A computer-implemented method is provided for estimating fluid flow into a production well flowing into a reservoir comprising fluid, the well comprising a central tube and an annulus surrounding the central tube. The annulus is connected to the reservoir to receive fluid at one or more inflow sites. The central tube has at least one inlet, arranged to allow fluid to flow from the annulus into the central tube, and is located downstream of one or more inflow sites. The production well further comprises one or more devices arranged to measure a temperature of fluid within the annulus at a plurality of points along the annulus length. The method comprises: receiving temperature data from one or more devices indicative of a temperature of fluid at a plurality of points along the length of the annulus; identify a change in temperature of fluid flowing within the annulus, based on the temperature data received at the plurality of points; employing a model for estimating heat transfer from the central tube to fluid flowing within the annulus, the model being arranged such that the heat transition is assumed to be substantially constant along the length of the tube; and estimate a rate at which fluid flows into the annulus from the reservoir at a first inflow site, on the basis of the identified change in temperature between the points and the estimated heat transfer.

Description

ESTIMATION OF FLOW IN PRODUCT JONSBRØNN

Technical area

The following describes systems and methods for estimating flow of fluid in a production well, and in particular for estimating flow based on temperature.

Background

Reservoirs, particularly hydrocarbon-bearing reservoirs, typically contain fluids such as oil, gas and water in layers of permeable reservoir rock. These layers can be separate, or partially connected, which means that the fluids can flow between layers at only a limited number of points. The layers may have different characteristics, such as permeability of the reservoir rock and viscosity of the fluid, and fluid may consequently flow along each layer at a different rate.

In some cases, waterflooding or similar secondary recovery techniques may be used to force additional fluid (hydrocarbons) out of the reservoirs. However, the effect of these techniques is reduced if the flood water is carried along a layer that is relatively more permeable than the layer occupied by hydrocarbons.

Techniques for enhanced oil recovery (EOR) can be used to increase the effect of the other recovery measures. These techniques include injecting aqueous solutions of polymers such as viscosifiers into the well to partially or completely block a higher permeability layer and thereby improve the recovery of hydrocarbons from the less permeable layer. Polymeric microparticles with labile (reversible) and non-labile internal crosslinks in which the microparticle conformation is limited by the labile internal crosslinks can be used, for example. The microparticle properties, such as the limited microparticle particle size distribution and density, are tailored to allow rational propagation through the pore structure of hydrocarbon reservoir matrix rock, such as sandstone. Upon heating to reservoir temperature and/or at a predetermined pH, the labile internal crosslinks begin to break, allowing the particles to expand by absorbing the injection fluid (usually water). The expanded particle is designed to have a particle size distribution and physical characteristics that allow it to prevent the flow of injected fluid into the pore structure of the high permeability reservoir layer. It can thus redirect later injected fluid to less carefully swept zones of the reservoir.

To ensure that these techniques are used effectively, it is important to know, or be able to estimate, the flow rate into a production well from the various layers. Prior methods involve providing flow meters at a number of points in the production well. Alternatively, a sensor can be lowered into a production well to measure flow at different points.

However, these methods can only provide rough measurements of the production rate, as a large number of flow sensors cannot be readily installed in a production well, and a sensor that needs to be lowered into a production well can only be lowered occasionally, e.g. when the well is shut off.

Recently, downhole temperature sensors have been installed in wells. These sensors measure the ambient temperature at a number of points along a well, typically at a distance of one meter or similar.

It is desirable to be able to use temperature data to estimate the flow rate in a production well.

Brief description of the embodiments

According to at least one embodiment, methods, devices, systems and software are provided to support or implement functionality to estimate the flow of fluid into a production well and to estimate the gradient in a reservoir.

This is achieved by a combination of features listed in each independent claim. Dependent requirements specify further detailed implementations.

According to a first embodiment, there is provided a computer-implemented method for estimating flow of fluid into a production well running into a reservoir comprising fluid, the well comprising a central tube and an annulus surrounding the central tube, the annulus being connected to the reservoir for to receive fluid at one or more inflow points, and the central pipe has at least one inlet, arranged to allow fluid to flow from the annulus into the central pipe, and is placed downstream of the one or more inflow points, the production well further comprising one or the several devices arranged to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the method comprising: receiving temperature data from the one or more devices indicative of a temperature of fluid at a plurality of points along the annulus length; identifying a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; applying a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being arranged so that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition.

According to another embodiment, there is provided a computer-readable storage medium that stores computer-readable instructions thereon for execution on a data processing system to implement a method of estimating flow of fluid into a production well running into a reservoir comprising fluid, the well comprising a central pipe and an annulus surrounding the central tube, the annulus being connected to the reservoir for receiving fluid at one or more inflow points, and the central tube having at least one inlet, arranged to allow fluid to flow from the annulus into the central tube, and is located downstream of the one or more inflow locations, the production well further comprising one or more devices arranged to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the instruction set being arranged to cause the data processing system to perform the steps of to: receive temperature data from the one or more devices indicative of a temperature of fluid at a plurality of points along the length of the annulus; identifying a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; applying a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being arranged so that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition.

According to a third embodiment, a system is provided for estimating flow of fluid into a production well that runs into a reservoir comprising fluid, the well comprising a central tube and an annulus surrounding the central tube, the annulus being connected to the reservoir to receive fluid at one or more inflow points, and the central pipe has at least one inlet, arranged to allow fluid to flow from the annulus into the central pipe, and is placed downstream of the one or more inflow points, the production well further comprising one or more devices which are arranged to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the system comprising: a boundary layer which is arranged to receive temperature data, the temperature data being collected by the one or more devices and being indicative for a temperature of fluid at a plurality of points along the length of the annulus; and a processor arranged to: identify a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; run a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being set up so that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition.

Further features and advantages of embodiments will be apparent from the following description, given only by way of example, which is given with reference to the accompanying drawings. Brief description of the drawings

Figure 1 shows a schematic diagram of an oil recovery system and reservoir with respect to which embodiments are applicable; Figure 2 shows a schematic diagram of a section of a production well; Figure 3 shows a schematic diagram of a section of a production well; Figure 4 shows a schematic diagram of a treatment system in which embodiments may operate; Figure 5 shows a computer-implemented method for estimating flow into a production well; Figure 6 shows a graph of temperature development over time; Figure 7 shows a computer-implemented method for estimating slope in a reservoir; and Figure 8 shows a schematic diagram of well locations in a reservoir in which embodiments can be used.

Several parts and components of embodiments are shown in more than one figure; for clarity, the same reference number will be used to refer to the same part and component in all figures.

Detailed description of illustrative embodiments

Before example embodiments are described in detail, embodiments will first be described in brief form.

According to a first embodiment, there is provided a computer-implemented method for estimating flow of fluid into a production well running into a reservoir comprising fluid, the well comprising a central tube and an annulus surrounding the central tube, the annulus being connected to the reservoir for to receive fluid at one or more inflow points, and the central pipe has at least one inlet, arranged to allow fluid to flow from the annulus into the central pipe, and is placed downstream of the one or more inflow points, the production well further comprising one or several devices arranged to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the method comprising: receiving temperature data from the one or more devices indicative of a temperature of fluid at a plurality of points along the annulus length; identifying a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; applying a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being arranged so that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition.

A production well will generally receive fluid (ie water, oil and/or gas) from the well at a number of discrete locations along the length of the borehole. These places can be defined by cracks in the underlying rock, which serve to transport the fluid towards the well. Fluid will flow from the cracks into the annulus. Within the annulus, the fluid from one crack can mix with fluid from other cracks, and will flow "downstream" along the annulus (downstream means towards the surface). The fluid then flows from the annulus to the central tube at one or more inlet points. The fluid will then flow downstream along the central tube to the surface.

These production wells may be equipped with "downhole temperature sensors"

(DTS), which are one or more devices that measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus.

To correctly understand (eg model) a reservoir it is important to understand not only the total flow of fluid out of the production well as a whole, but the flow into the well at each inflow point (eg fracture). One reason for this is that reservoirs are typically layered (ie they have layers of permeable and impermeable rock), and fluid only flows along, and from, the permeable layer. By understanding the flow at each inflow point, the composition of the layers can be better understood, and the operation of the wells can thus be made more rational.

At a given point, the fluid within the central tube will be hotter than the fluid within the annulus, as it originates from a deeper point in the reservoir. There is thus a temperature gradient between the central tube and the fluid in the annulus. This temperature gradient causes heat to flow from the central tube to the fluid in the annulus.

By identifying a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points and using a model to estimate heat transfer from the central tube to fluid flowing within the annulus along the length of the tube, embodiments can estimate a flow rate for fluid along the annulus at the point, as the change in temperature will be greater when the flow rate along the annulus is lower, and correspondingly less when the flow rate along the annulus is higher. Such embodiments can therefore estimate a rate at which fluid flows into the annulus at a mentioned inflow point from the change in temperature between the point and the estimated heat transition.

Embodiments can thus estimate the flow of fluids into a well using a relatively simple measuring system (the temperature sensor).

In embodiments, the method may comprise using the model to determine a specific heat capacity for the fluid and thereby estimate a composition of the fluid flowing from the reservoir into the annulus at the first inflow location.

The composition of the fluid (ie the oil/water/gas mixture) may vary during the life of the well. The composition of the fluid can also change between layers. The fluid's composition will affect the fluid's specific heat capacity, and the temperature changes accordingly. By looking at how temperatures change, the composition of the fluid that flows into and along the well can therefore be estimated and thus provide data that can be used to increase the efficiency when extracting fluid from the well.

In embodiments, the method may include: using the model to estimate a rate at which the fluid flows along the longitudinal axis of the annulus, thereby estimating a rate at which fluid flows into the annulus at the first inflow location.

In embodiments, the method may comprise: identifying a temperature of fluid within the central tube; and determining a temperature gradient between the fluid within the central tube and the fluid within the annulus, whereby heat transfer from the central tube to fluid flowing within the annulus is estimated.

The fluid in the central pipe and in the annulus will generally be at different temperatures, the central pipe, as it carries fluid further down the well, will typically be at a higher temperature. The central pipe will thus heat up the fluid in the annulus as the fluid is guided along the annulus. By looking at the temperature change rate of the fluid in the annulus, the flow rate along the annulus can be estimated. By identifying the central pipe temperature, a more accurate estimate can be made.

In some embodiments, the temperature of the fluid in the central tube can be identified by direct measurement, ie by using an additional downhole temperature sensor, or by inserting a probe into the central tube at certain intervals. Alternatively or in addition, the temperature can be estimated on the basis of temperature measurements taken in parts of the annulus upstream of the point in question. The fluid in these parts of the annulus will be assumed to have been introduced into the annulus by an inlet which is located upstream of the point in question.

In embodiments, the method may comprise identifying a change in temperature of fluid within the annulus between a point upstream of the first inflow location and a point downstream of the first inflow location; applying a further model to estimate a change in temperature of the fluid in the annulus caused by fluid entering the annulus from the reservoir at the first inflow location; estimate a rate at which fluid flows into the annulus at the first inflow location, based on the identified change in temperature and the predicted change in temperature.

In embodiments, the method may comprise identifying a geothermal temperature at a depth corresponding to the first inflow location, thereby estimating a temperature of fluid flowing into the annulus at the first inflow location, wherein the further model is configured to estimate the change in temperature of the fluid in the annulus based on the temperature of the fluid entering the annulus at the inflow point.

The fluid flowing from the reservoir will be at the geothermal temperature corresponding to the depth of the inflow point (within a given margin of error). This geothermal temperature will be known from surveys etc. When the fluid enters the annulus, it will change the temperature of the fluid in the annulus, either by mixing with a flow of fluid within the annulus, or by displacing a stagnant portion of fluid. The flow rate of fluid into the annulus can be estimated using knowledge of the temperature of the fluid entering the annulus, and from the temperature change in the fluid in the annulus.

In embodiments, the further model may be arranged: such that fluid flowing within the annulus is assumed to be mixed with fluid entering the annulus at the first inflow point, and associate the change in temperature of the fluid within the annulus with a flow rate and a temperature of fluid flowing within the annulus upstream of the first inflow point, and a flow rate and temperature of fluid flowing into the annulus at the first inflow point.

In embodiments, the method may comprise applying a still further model to estimate a change in temperature of fluid flowing into the annulus at the first inflow location, the still further model accounting for Joule-Thompson expansion of fluid flowing into the annulus at the first inflow point.

One advantageous method by which the flow rate can be estimated is by looking at the Joule-Thompson effect on the fluid as it flows from the reservoir into the annulus. The Joule-Thompson effect will change the temperature of the fluid and thus make it possible to estimate the flow rate.

In embodiments, the method may comprise using said model to refine an estimate of a rate at which fluid flows into the annulus at the first inflow location generated by a further said model.

In embodiments, the method may include using a mentioned model and/or a mentioned additional model whereby a rate at which fluid flows into the annulus at one or more other inflow points is estimated.

In embodiments, the method may comprise using the model and/or the further applied model to estimate a rate at which fluid flows into the annulus at one or more second inflow locations whereby the estimate of the rate at which fluid flows into the annulus at the first inflow location is refined .

The rate at which fluid flows into the annulus at a given inflow point can affect the changes in temperature at locations downstream of the given inflow point. An improved estimate of the rate at which fluid flows into the annulus at the first inflow location can therefore be made by using further applied models to estimate the rate at which fluid flows into the annulus at one or more other inflow locations.

In embodiments, the method may comprise estimating a set of values for rates at which fluid flows into the annulus at the first inflow location, each value being associated with data indicative of a composition of the fluid flowing into the annulus at the first inflow location.

In embodiments, there are a number of unknown variables, not only the flow rate, but the fluid composition, and any changes in the reservoir temperature (described in more detail below). A set of values for rates at which fluid flows into the annulus can thus be estimated, each value being associated with data indicative of a composition of the fluid flowing into the annulus at the first inflow point.

On the basis of further measurements taken elsewhere in the borehole, or knowledge of the composition of the fluid entering the well (from e.g. a historical analysis), some of the values in this set can then be excluded to refine the set.

The process can be iterative, i.e. as more data is received and more temperature changes are identified, the sets can be gradually improved.

In embodiments, the annulus may be divided into a plurality of sections, each section having one or more inflow points, and the central pipe having an inlet which is open to the annulus, and which is located at the downstream end of each section, the method may include: estimating flow rate of fluid from the reservoir into a first said section; estimating a flow rate of fluid from the first section into the central tube through a first said inlet from the flow rates of fluid from the reservoir into the first section; estimating a flow rate of fluid within the central tube downstream of the first section based on the estimated flow rate of the fluid through the first inlet of the first section; estimating flow rates of fluid within a second said section using the estimated flow rate of fluid within the central pipe.

In some embodiments, the annulus is divided into sections. Fluid cannot generally be passed from one section to another, e.g. is the section isolated (it should be understood that a small amount of fluid can pass the separations). Each section can thus be analyzed essentially independently. A determined flow rate in one section can also be used to determine a flow rate along the central pipe, and thus in determining a flow rate in a downstream section. In embodiments, the process of estimating the flow rates thus starts with the section located at the upstream end of the well (eg at the deepest point), and the result for each section is used in subsequent sections.

In embodiments, the method may include receiving data indicative of, or one or more of, measurements of the temperature, composition, and flow rate of fluid in the central tube, and using the measurement data to validate data generated by the models.

In some embodiments, the temperature, composition and flow rate of fluid in the central tube can be measured. This can be done at the surface by taking a sample of the fluid produced by the well. The measured data can be used to estimate the flow rate in the production well. In some embodiments, such measured data can be used to modify a set of flow rate values to improve accuracy.

In embodiments, the method may include: receiving temperature data for fluid flowing into the annulus at the first inflow location at a plurality of times; and identifying a change over time in a temperature of the fluid flowing into the annulus at the first inflow location.

In embodiments, the method may include: identifying a flow rate of fluid entering the production well at the first inflow location at each of the plurality of times; identify a geothermal gradient indicative of a change with depth in temperature of rock within and around the reservoir; and determining a measure of the slope in a layer of the reservoir based on the change over time in the temperature, the geothermal gradient and the flow rate.

The temperature of the fluid entering the well can change over time. By monitoring the temperature, and thus the flow rates, such changes in temperature can be identified. These temperature changes can be used to determine information about the reservoir. The slope of the reservoir can, for example, be determined from the development of the fluid temperature over time. The "slope" of the reservoir indicates that the depth of the reservoir is not constant. The temperature development is therefore caused by fluid that is carried along the reservoir from a deeper or shallower point to the inflow point. The development can take many days, and perhaps years, as it takes time for the fluid to flow to the inflow site. The slope of the reservoir can thus be determined from the change in temperature, and the modeling and mapping of the reservoir can thus be improved.

According to another embodiment, there is provided a computer-readable storage medium that stores computer-readable instructions thereon for execution on a data processing system to implement a method of estimating flow of fluid into a production well running into a reservoir comprising fluid, the well comprising a central pipe and an annulus surrounding the central tube, the annulus being connected to the reservoir for receiving fluid at one or more inflow points, and the central tube having at least one inlet, arranged to allow fluid to flow from the annulus into the central tube, and is located downstream of the one or more inflow locations, the production well further comprising one or more devices arranged to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the instruction set being arranged to cause the data processing system to perform the steps of to: receive temperature data from the one or more devices indicative of a temperature of fluid at a plurality of points along the length of the annulus; identifying a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; applying a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being arranged so that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition.

In embodiments, the instruction set may be arranged to cause the computing system to apply the model to determine a specific heat capacity for the fluid and thereby estimate a composition of the fluid flowing from the reservoir into the annulus at the first inflow location.

In embodiments, the instruction set may be arranged to cause the computing system to apply the model to estimate a rate at which fluid flows along the longitudinal axis of the annulus, thereby estimating a rate at which fluid flows into the annulus at the first inflow location.

In embodiments, the instruction set may be arranged to cause the data processing system to: identify a change in temperature of fluid within the annulus between a point upstream of the first inflow location and a point downstream of the first inflow location; applying a further model to estimate a change in temperature of the fluid in the annulus caused by fluid entering the annulus from the reservoir at the first inflow location; and estimating a rate at which fluid flows into the annulus at the first inflow location, based on the identified change in temperature and the predicted change in temperature.

In embodiments, the instruction set may be configured to cause the computing system to: identify a geothermal temperature at a depth corresponding to the first inflow location, thereby estimating a temperature of fluid flowing into the annulus at the first inflow location, wherein the additional model is configured to estimate the change in temperature of the fluid in the annulus based on the temperature of the fluid entering the annulus at the point of inflow.

In embodiments, the further model may be arranged so that fluid flowing within the annulus is assumed to be mixed with fluid entering the annulus at the first inflow point, and associate the change in temperature of the fluid within the annulus with a flow rate and a temperature of fluid flowing within the annulus upstream of the first inflow point, and a flow rate and temperature of fluid flowing into the annulus at the first inflow point.

According to a third embodiment, a system is provided for estimating flow of fluid into a production well that runs into a reservoir comprising fluid, the well comprising a central tube and an annulus surrounding the central tube, the annulus being connected to the reservoir to receive fluid at one or more inflow points, and the central pipe has at least one inlet, arranged to allow fluid to flow from the annulus into the central pipe, and is placed downstream of the one or more inflow points, the production well further comprising one or more devices which are arranged to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the system comprising: a boundary layer which is arranged to receive temperature data, the temperature data being collected by the one or more devices and being indicative for a temperature of fluid at a plurality of points along the length of the annulus; and a processor arranged to: identify a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; run a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being set up so that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition.

In embodiments, the processor may be arranged to apply the model to determine a specific heat capacity for the fluid and thereby estimate a composition of the fluid flowing from the reservoir into the annulus at the first inflow location.

In embodiments, the processor may be arranged to use the model to estimate a rate at which the fluid flows along the longitudinal axis of the annulus, thereby estimating a rate at which fluid flows into the annulus at the first inflow location.

In embodiments, the processor may be arranged to: identify a change in temperature of fluid within the annulus between a point upstream of the first inflow location and a point downstream of the first inflow location; running a further model to estimate a change in temperature of the fluid in the annulus caused by fluid entering the annulus from the reservoir at the first inflow location; and estimating a rate at which fluid flows into the annulus at the first inflow location, based on the identified change in temperature and the predicted change in temperature.

In embodiments, the processor may be arranged to: identify a geothermal temperature at a depth corresponding to the first inflow location, thereby estimating a temperature of fluid flowing into the annulus at the first inflow location, wherein the further model is configured to estimate the change in temperature on the fluid in the annulus based on the temperature of the fluid entering the annulus at the inflow point.

In embodiments, the further model may be arranged so that fluid flowing within the annulus is assumed to be mixed with fluid entering the annulus at the first inflow point, and associate the change in temperature of the fluid within the annulus with a flow rate and a temperature of fluid flowing within the annulus upstream of the first inflow point, and a flow rate and temperature of fluid flowing into the annulus at the first inflow point.

Figure 1 is a schematic block diagram showing a simplified representation of a fluid recovery system 1 comprising a multilayer reservoir. In this example, the reservoir comprises a series of embedded permeable and impermeable layers. The permeable layer carries fluid (such as oil, gas and water) in the pore spaces within the rock and has the reference numbers 2 and 4. The impermeable layers have the reference numbers 6, 8 and 10. Above the upper impermeable layer 6 there is a generalized surface layer 12 which can include several non-oil-bearing layers, and (if the reservoir is offshore) a layer of seawater. The composition of this layer 12 is not relevant for this example.

The permeable and impermeable layers make up the reservoir. The reservoir is penetrated by an injection well, comprising a control station 14 and a borehole 16, and a production well, comprising a control station 18 and a borehole 20. The injection and production wells are separated by a distance L as shown. There are typically many more wells than the two shown here; however, two are shown in this example embodiment for simplicity.

When the injection well is used for a water flood, it injects water as injection fluid under pressure into the reservoir. The water flows along each of the permeable layers 2 and 4 as shown by the arrows. The water pushes the oil in the reservoir ahead of it and causes the oil to be displaced from the reservoir into the production well's borehole (again shown by the arrows). From there, the reservoir's pressure, possibly aided by pumps placed in the production well's borehole, lifts the oil and water produced from the reservoir up to the surface where it can be stored and refined.

The composition of the production well borehole 20 will now be described in more detail with reference to figure 2.

Figure 2 is a schematic diagram showing a simplified representation of a portion of a borehole 20 in a production well. The borehole comprises an annulus 22 which opens towards the rock of the reservoir. Along the annulus runs a central pipe 24 which transports fluid to the surface. The annular space is thus located between the central pipe 24 and the borehole.

The borehole can be an open borehole, i.e. one that is not lined with casing. The annulus is divided into sections, with section 26 being fully represented, and the surrounding sections 28 and 30 being partially represented in Figure 2. The section is separated by separators (also known as "gaskets") 32 (between sections 26 and 28) and 34 (between sections 26 and 30), which isolate a given section from adjacent sections. The flow of fluid within a given section is thus isolated from the flow of fluid in other sections. In this example, the packing 32 is designated the downstream packing for section 26, and the packing 34 is designated the upstream packing for section 26. As is well known in the art, downstream and upstream are measured in relation to the flow of fluid in the well, and the upstream packing is thus generally placed at a greater depth than the downstream packing.

Down the borehole, through the annulus, goes a downhole temperature sensor (DTS) 36. The DTS can measure the temperature of the fluid in the annulus at a plurality of points along its length. The DTS can typically be a fiber optic sensor, as is known in the art.

As described above, the annulus 22 is open to the rock of the reservoir, which means that fluid can flow into the annulus from the reservoir. While a small amount of fluid may enter the annulus along its entire length, most of the fluid will enter the annulus at a number of inflow points, which are typically cracks in the rock that provide a low-permeability pathway into the annulus and thus carry most of the flowing fluid from the reservoir into the annulus 22. Two such inflow locations (i.e. cracks) are shown by arrows 38 and 40.

Fluid that has entered the annulus 22 can flow downstream along the annulus towards an inlet 50 in the central pipe. At the inlet, the fluid can enter the central tube from the annulus. The fluid in the central tube can thus be transported to the surface. This process will be described in more detail with reference to figure 3.

Figure 3 shows a two-dimensional section of the borehole similar to Figure 2. Similar features are provided with similar reference numbers and will not be described in detail, it being sufficient to say that the annular space 22 surrounds the central pipe 24. The annular space is divided by the seals 32 and 34 in sections 26, 28 and 30, and a DTS 36 is provided along the longitudinal length of the annulus.

Fluid is shown flowing into the annulus at the two inflow locations 38 and 40. The first location 38 is at a greater depth than the second location 40 and is thus upstream of the second location 40. While only two inflow locations are shown, it will be apparent that many more may be present in any given section of the annulus. While the inflow locations are shown only on one side of the annulus, it should also be understood that a crack forming an inflow location may be present around some, or all, of the annulus 22 circumference.

The flow within the annulus section 26 will now be described in more detail. In the upstream end of the annulus (lower part of figure 3) the flow of fluid is stagnant. This is because there is no inflow of fluid through the packing 34, and this part of the annulus is upstream of the first inflow point 38. This stagnant fluid is represented by loop arrow 42.

Fluid flows from the reservoir into the annulus at the first inflow point 38. The fluid then flows downstream (ie, upwards) along the annulus, as represented by arrow 44.

At the second inflow point 40, further fluid flows into the annulus 22. This fluid mixes with the fluid that is already flowing up the annulus 44.

The fluid flows to the annulus' downstream end where, as represented by arrow 48, it flows into the central tube via an inlet 50.

As represented by arrow 52, fluid additionally flows up the central tube from sections located upstream of the section 26 considered here. The fluid from section 26, which enters the central tube as represented by arrow 48, mixes with the flow 52 already in the central tube 24 and will continue to rise until it reaches the surface.

DTS 36 measures the temperature of the fluid in the annulus at a plurality of locations, with reference number 37A..E. It should be understood that these points are only examples, and the temperature can be measured at many other points in the annulus 22. Point 37A corresponds to the point at which the fluid in the annulus is stagnant (ie flow 42). Point 37B corresponds to a point just downstream of the first inflow 38. Point 37C corresponds to the point just upstream of the second inflow 40. Point 37D corresponds to a point just downstream of the second inflow 40. Point 37E finally corresponds to a point just upstream of the inlet 50 .

Embodiments provide computer systems and computer-implemented methods that can be used to assist in the estimation of flow in a production well as described above. To this end, embodiments may include a computer system running flow estimation (FE) software components that enable the system to estimate the flow into and within the production well.

The computer system may be located in a planning and control center (which may be located a significant distance from the reservoir, including in another country). Alternatively, the computer system may be part of the reservoir's control systems, such as the control stations 14 and 18 as shown in Figure 1. The FE software components may include one or more applications known in the art, and/or may include one or more additional modules for existing software.

A schematic block diagram showing such a computer system will now be described with reference to Figure 4. The computer system 200 comprises a processing unit 202 with a processor, or CPU, 204 which is connected to a volatile memory (ie RAM) 206 and a non- volatile memory (such as a hard disk) 208. The FE software components 209, which carry instructions for implementing embodiments, may be stored in the non-volatile memory 208. The CPU 204 is additionally connected to a user interface 210 and a network interface 212. The network interface 212 can be a wired or wireless interface and is connected to a network, represented by cloud 214. The processing unit 202 can thus be connected to sensors, databases and other sources and recipients of data through the network 214.

In use, and according to standard procedures, the processor 204 retrieves and executes the FE software components 209 stored in the non-volatile memory 208. During the execution of the FE software components 209 (ie, when the computer system performs the actions described below) the processor may store data temporarily in the volatile the memory 206. The processor 204 may also receive data (as described in more detail below) through the user interface 210 and the network interface 212 as needed to implement embodiments. Data can, for example, be entered by a user through the user interface 210 and/or received from, for example, a downhole temperature sensor in a production well through the network 214 and/or can be retrieved from an external database through the network 214.

This data can be generated and/or stored in a number of ways known to those skilled in the art. Diffusion coefficients (described below) can, for example, be determined in a laboratory from a core sample of the reservoir using well-known processes. As soon as this data is determined, it can be actively sent to the processing unit 202 or stored in a database to be retrieved as needed by the processing unit 202. Alternatives will be readily apparent to the person skilled in the art.

After processing the data, the processor 204 can provide output via either the user interface 210 or the network interface 212. If necessary, the output data can be transferred over the network to external stations, such as the control station for an injection well. Such processes will be readily apparent to the person skilled in the art and will therefore not be described in detail.

Examples of the computer-implemented methods that estimate flow rates within section 26 will be described below with reference to Figure 5. To put these example methods into context, however, the temperature changes associated with the flow of fluid into and along the annulus will first be described for a section with two inflow locations (as represented above by arrows 38 and 40), and a stream of fluid coming from upstream in the central tube (as represented above by arrow 52).

The downhole temperature sensor (DTS) 36 in the annulus measures temperature along the annulus and in particular the following changes in temperature: (i) a relatively abrupt change (ie a jump) in the temperature of the fluid in the annulus at the first inflow point 38; (ii) a change (ie, an evolution) in temperature of the fluid in the annulus between the first inflow point 38 and the second inflow point 40 due to heat transfer from the central tube to the annulus (ie, along arrow 44); (iii) a second relatively abrupt temperature change at the second inflow location 40; and (iv) development of temperature downstream of the second inflow location 40 towards the point where the annulus flow enters the main tube (ie along arrow 46) due to heat transfer from the central tube to the annulus.

It should be understood that in embodiments several inflow locations may be present, there will therefore be several temperature jumps, and temperature developments. Nevertheless, only two locations will be relevant for this example.

It is assumed that the nature (ie temperature, flow rate and/or composition) of the fluid flowing from further upstream (represented by arrow 52) is known. This is because for any given section of the annulus, the process described herein can estimate the nature of the fluid flowing into that section from the reservoir, and estimate the nature of the fluid entering the central tube from that section. The procedure described herein can therefore be carried out section by section along the well, starting with the foot (ie bottom) of the well (ie the section furthest upstream) where the flow in the central pipe 24 is known (and is zero). The analysis of this section furthest upstream can be used to estimate the nature of the fluid entering the central pipe 24 from this section. The nature of the fluid in the central pipe 24 which is carried to the next downstream section is therefore known. The process can be repeated for each section working downstream, the fluid entering the annulus at any given section mixing with the fluid in the central pipe 24 and proceeding downstream from that section. As each section is analyzed, the composition, flow rate and temperature of the fluid in the central pipe 24 can thus be determined.

The temperature of the flow 52 in the central pipe 24 at the upstream packing 34 is denoted Tog the flow rate Q. It will also be assumed that the flow 52 has a known composition (i.e. mixture of oil, gas and water) and thus a specific heat capacity (which can be a average heat capacity of the mixed fluids). The reservoir's geothermal temperature is higher at greater depths. The fluid in the central tube will therefore, after flowing from these greater depths, be at a higher temperature than the fluid in the annulus.

As described above, the region 42 between the upstream packing and the first inflow point 38 is approximately stationary and will thus over time assume the temperature T in the central pipe. This temperature can be measured with the DTS 36 as soon as the flow in the well has stabilized, which means when the fluid in region 42 has had the chance to be heated by the flow in the central pipe 24.

At the first inflow point 38, the temperature in the annulus will jump to the value T}, which is close to the geothermal temperature ( TGj ) at that depth, but may differ due to the Joule-Thomson effect which cools the fluid as it flows from the reservoir rock into the the annulus at the inflow point, and to a temperature drift in the geothermal. This Joule-Thomson effect can cause a temperature change which can be represented in terms of a Joule-Thomson coefficient JT, this being a function of the composition of the fluid flowing into the annulus at the first inflow point 38. The temperature Ti at the first the inflow point can thus be given by the formula:

where:

Ti is the temperature of the fluid at the first inflow point 38;

TG] is the geothermal temperature at the depth of the first inflow site 38;

DTirepresents a quantity of temperature drift (which will be discussed below);

JT is a Joule-Thomson coefficient for the composition of the fluid entering the annulus at the first inflow point 38, which can be determined from the composition of the fluid; and

Qi represents the flow rate of fluid into the annulus at the first inflow point 38.

The geothermal temperature TGikan is determined using methods known in the art; it can, for example, be calculated from survey data or, as the geothermal temperature is relatively static, it can be measured as the well is drilled, or before flow starts in the well. A range of values for JT, Qi and DTis consistent with Ti to within a specified error tolerance, can therefore be determined using the above formula. In the early stages of fluid extraction from the reservoir, the flow into the annulus is likely to be pure oil (perhaps containing dissolved gases), as JT will therefore be known; the temperature drift DT} will likewise be small. An estimate or range of values for Qii compliance with Ti can therefore be determined (since JT for pure oil is known). At later times, JT can be determined from measurements made at the surface of the composition of the fluid in the production well, and from observation of the development of the flow of fluid in the production well.

The temperature change at the first inflow location 38 can be determined using, for example, the temperature measured with the DTS 36 at points 37A and 37B as described above in Figure 3.

The flow 44 between the first and second inflow locations 38 and 40 can then be analyzed. The fluid flowing within region 44 will initially start at temperature Ti and will have a flow rate of Qi. Since the temperature (T) in the central tube 24 is greater than the temperature (7;) in the annulus, there will, however, be a transfer of heat from the central tube to the annulus.

This transfer of heat can be modeled by, for example, assessing the heat transfer per unit distance (Qpa) along the pipe. Qpakan is calculated using a formula such as:

where:

Qpaer the heat transfer per unit distance; r is the outer radius of the central tube 24; k is the thermal conductivity of the central tube 24; 8 is the thickness of the central tube 24 wall;

T is the temperature of the fluid in the central tube 24; and

Ta is the temperature of the fluid in the annulus at a given point along the length of the annulus.

The temperature change for the fluid in the annulus can additionally be modeled using the following:

where:

Qpaer the heat transfer per unit distance (as calculated above using equation 2);

p is the density of the fluid in the annulus 22;

Ma is the volume flux in the annulus (ie the volume flux for example for flow 44 in Figure 3); and

dT

—- is the temperature change per unit length for the fluid in the annulus (length is measured dz

here along the longitudinal axis of the annulus).

It will clearly appear that the higher the rate at which the fluid flows along the annulus (ie the greater the value of Ma), the smaller the temperature change rate with height. By comparison, a relatively low flow rate will result in a relatively greater change in temperature.

Equations 2 and 3 above can be used to refine the values of Qi calculated using Equation 1 and also the composition of the fluid as determined according to the techniques described above.

At the second inflow point 40, fluid flows into the well with a flow rate of Q2, at a temperature T2, and with a certain composition. As above, T2 represents the temperature of the fluid entering the annulus at a location corresponding to the second inflow location 40, and thus takes into account the Joule-Thomson effect and geothermal drift at that location. This fluid mixes with the fluid in the annulus and causes the temperature in the annulus to change abruptly.

The abrupt change in temperature (AT2) associated with the second inflow site 40 can be modeled by:

where:

T12 is the temperature of the fluid in the annulus at a point just upstream of the second inflow point 40;

AT2 is the abrupt change in temperature at the second inflow location 40;

CP] is the specific heat capacity of the fluid upstream of the second inflow point 40, which can be calculated from the composition of the fluid at that point upstream;

CP2 is the specific heat capacity of the fluid entering the annulus at the second inflow point 40, which can be calculated from the composition of the fluid;

Q2 is the flow rate of the fluid entering the annulus at the second inflow point 40; and

T2 is the temperature of the fluid entering the annulus at the second inflow point 40;

Using equation 4, a range of values for Q2, T2 and CP2 can be estimated for fluid at the second inflow point 40. From CP2, the composition of the fluid entering the annulus at the second inflow point 40 can also be estimated.

The temperature change at the second inflow location 40 can be determined using, for example, the temperatures measured with the DTS 36 at points 37C and 37D.

In a similar manner as described above, the flow upstream of the second inflow point 40 (ie between the second inflow point 40 and the inlet of the central pipe 50) will develop in temperature as heat is transferred from the central pipe 24 to the fluid in the annulus 22. This transfer of heat can be modeled using equations 2 and 3 above and used to refine the value for Qi and Q2 and for the composition of the fluid as calculated above.

These measurements and calculations can be repeated for inflow locations between the second inflow location 40 and the inlet of the central pipe 50.

The estimated flow rates into the annulus {Qi and Q2) can be used to determine the flow rate of fluid from the annulus 22 into the central tube 24, while the temperature of the fluid flowing into the central tube can be determined from measurements made by the DTS 36. These values can be combined with the flow rate Q and temperature T in the central pipe 24 to determine the flow rate and temperature of the fluid in the central pipe 24 downstream of the inlet 50. The flow rate and temperature of the fluid in the central pipe within the downstream sections can therefore be determined. The steps described above can be repeated for each section of the annulus proceeding downstream, the estimates of flow rate and temperature in a given section of the annulus being used to estimate the temperature and flow rate in the central tube for downstream sections.

It should be understood that the temperature changes are dependent on the flow rate of the fluid into the central pipe 24, the composition of the fluid and any geothermal operation. At each inflow point, or along the annulus between inflow points, a range of values for flow rate, composition, etc. can therefore be estimated. These ranges of values can be arranged in pairs, ie so that a certain composition is associated with a certain flow rate. These ranges of values can then be refined using measurement data which will be described in more detail below.

As described above, the temperature at any location along the annulus is dependent on the flow rate and composition of the fluid upstream of that location. The temperature change at the second inflow location 40 is, for example, partially dependent on the flow rate and composition of the fluid entering the annulus at the first inflow location 38. The calculations generated using data measured and estimated at any given location can thus be used to refine the range of values calculated further upstream of the given location.

For example, if a range of values for Qi is determined for the first inflow site, but parts of that range of values for Qi are not in

accordance with the temperature change observed at the second inflow location 40, the range of Qi can be modified to remove the inconsistent values. In practice, this may involve defining a set of values for Qikan to take, and then selecting a subset of the values to ensure that only matching values are retained.

Other measurements can also be taken and used to modify or improve the estimates for the composition and flow rate into the borehole. Surface measurements of total flow rate and overall composition from the borehole can, for example, be used to modify the flow rate and/or composition values calculated for a specific section or also a specific inflow location. In some cases, an overall model of the overall flow in the annulus can be constructed based on the principles described above, and the values entered into this model adjusted to achieve the best fit to the temperature data.

In some embodiments, temperature data is received for a number of time points and can be used in a model to determine the evolving flow field conditions (ie, flow rate and composition) in the borehole. The changes can be used to refine current and historical values for the composition and flow rate and identify gradual changes in, for example, the temperature of the fluid.

A method of estimating the flow of fluid from a reservoir into a section of an annulus (such as section 26 described above) performed by computer system 200, according to one embodiment, will now be described with reference to Figure 5.

In a first step 54, and according to the instruction set defined by the FE software components 209, the processor 204 receives temperature data from the DTS 36. The temperature data includes data indicative of the temperature of the fluid in the annulus 22 at a plurality of points within the annulus at a given time. The points may include points 37A..E as described above in figure 3.

In step 56, the processor 204 then uses the received temperature data to identify changes in the temperature of the fluid within the annulus 22 between the points, at any given time. At least one such identified change may correspond to a change in temperature associated with fluid entering the annulus from the reservoir such as the change in temperature between points 37A and 37B, and/or between points 37C and 37D described above with reference to Figure 3. At least one further such change may correspond to the transfer of heat from the central tube to the fluid in the annulus, such as the change in temperature between points 37B and 37C, and/or between points 37D and 37E described above with reference to Figure 3.

In step 58, the processor 204 selects an inflow location for modeling. The selected first inflow location may correspond to the inflow location 38 most upstream of the annulus 26 section. By selecting the first inflow location, the processor 204 can analyze the temperature data to look for locations (eg, locations 37A and 37B) between which there is a relatively large change in temperature.

As can be seen in Figure 5, steps 60 to 66 can be repeated for a number of inflow locations. These steps will therefore be described below for a first and a second inflow location. It will be assumed that the first inflow point is the inflow point most upstream of the annulus section, i.e. inflow point 38, and that the second inflow point has at least one inflow point upstream of it, i.e. inflow point 40.

In step 60, the processor applies a model for the temperature change for fluid flowing into the annulus 22 at the selected inflow location.

In the event that the selected inflow location is the most upstream inflow location in the annulus section (ie, first inflow location 38), the model may be configured to assume that the fluid flowing into the annulus (reference 38 in Figure 3) displaces the stagnant fluid within the annulus (reference 42 in Figure 3). The model can therefore be designed to assume that the temperature of the fluid downstream of the chosen inflow point is the temperature of the fluid that flows into the annulus, and that allows for a possible Joule-Thomson effect (since this is caused by the fluid entering in the annulus, expanding as it leaves the reservoir rock). Equation 1 above can therefore be used to relate the temperature of the fluid within the reservoir

(ie the temperature measured at point 37B) with the flow rate Qihos the fluid entering the reservoir.

In case the selected inflow point is not the most upstream inflow point in the annulus section (eg, inflow point 40); the model can be designed to assume that the fluid that flows into the annulus (reference 40 in Figure 3) mixes with fluid that flows within the annulus (reference 44 in Figure 3). Equation 4 as described above can therefore be used to relate the change in temperature (ie the change in temperature between points 37C and 37D) with the expected change in temperature caused by mixing of the fluid in the annulus (which has a previously estimated flow rate Qi, temperature and composition) with the fluid from the reservoir (for which the flow rate Q„ and the composition are to be estimated). In line with the description above, equation 1 can be used in conjunction with equation 4 to estimate any Joule-Thomson effect on the fluid flowing into the annulus.

In step 62, the processor applies the model described above with reference to step 60 to estimate the flow Q„ and the composition of the flow into the annulus at the selected (n-th) inflow location based on the temperature change between points, identified in step 58 above, corresponding to a change in temperature associated with fluid entering the annulus from the reservoir.

In step 64, the processor 204 applies an additional model of the heat transfer from the central tube to fluid in the annulus downstream of the nth inflow location (ie, between the nth inflow location and the next downstream inflow location, or the inlet of the central tube, if is relevant). To model the heat transfer, the model can be set up so that the heat transfer from the central pipe to the fluid in the annulus is assumed to be essentially constant along the length of the pipe. This preferably involves using equations 2 and 3 as set out above.

In step 66, the processor 204 may then apply the additional model to estimate and/or refine an estimate of the flow into the annulus at the first through the nth inflow locations (ie, Qi..„) based on the temperature change between points, identified in step 58 above, corresponding to the transfer of heat from the central tube to the fluid in the annulus and the modeled temperature change. This step may involve estimating the flow rate Q„ and estimating the composition of the fluid.

In step 70, it is determined whether temperature data is available from other inflow sites, and if so, processor 204 selects the next (ie, n+1) inflow site and proceeds to perform the steps described above from step 60. If there are no more inflow sites, the processor 204 can perform a similar analysis for other sections of the annulus, represented by the arrow returning to the starting point.

It should be understood that the above method can be used iteratively to generate and refine estimates of the flow rate of fluid into the well. For example, the estimate of a flow rate into the well (and of the composition of the fluid) generated by the model in step 60 for the first inflow site can then be refined using the model of the heat transfer from the central pipe in step 64, as Qi and the composition of the fluid will be modeled in both steps.

The output from the model of the temperature change at the second inflow point (step 60, for n = 2) can likewise be used to refine the previously calculated value of Qi, that is, the value of Q calculated with respect to the first inflow point 38. To this end, a series of fluid composition and flow rate values are estimated by the processor 204 at each step. This range may comprise a set of pairs of values, each pair being an estimate of flow rate and a corresponding composition. This range or set can be refined by excluding values that are inconsistent with values generated by subsequent iterations of the models.

In some embodiments, measurements may be made of, for example, the temperature in the central pipe, a flow rate in the central pipe (measured with a flow meter) and/or the composition of the fluid from the central pipe (eg, measured from a sample taken at the surface). These measurements can be used to refine the estimates, or ranges of estimates provided by the steps described above.

For example, if a set of values generated in steps 60 and 62 above for the flow rate and composition of fluid flowing into the annulus at a given inflow location contains one or more pairs of composition and flow rate values indicative of the fluid with a large proportion of water; and the fluid produced at the surface from the central tube is almost pure oil (ie has a small proportion of water), these pairs of composition and flow rate values can be ruled out as inconsistent with the surface measurements.

In some embodiments, the temperature data may be collected for a plurality of times. From these data, past flow rates can be refined by, for example, assuming that all changes (in flow rate or composition) are gradual and continuous. Subsequent modeling steps can thus be used to refine previous models.

In some embodiments, a series of temperature measurements may be taken for a number of time points. From these measurements, estimates can be made for changes in the temperature of the fluid entering the well. These changes were represented as factor DTi, namely temperature drift, in equation 1 above. In some embodiments, the changes in the temperature of the fluid entering the well can be determined by the processor 204 from the DTS data in connection with the determination of estimates for the flow rates in the annulus.

The changes in DTikan are then used to estimate the reservoir slope. If we return to Figure 1, it can be seen that the reservoir layer cannot be horizontal between the injection well and the production well. It can be seen, for example, that the reservoir's layer 2 changes depth. In this context, slope is a measure of the gradient, or rise, in the depth of the reservoir in relation to a horizontal line joining the injection well and the production well.

Before fluid is extracted from the reservoir, the fluid in the reservoir layer will be at the geothermal temperature (ie the fluid will have achieved thermal equilibrium with the surrounding rock in its source position in the reservoir). As the geothermal temperature increases with depth, the temperature of fluid in a reservoir will change as the depth of the reservoir changes. It can therefore be expected that in the example shown in figure 1 the fluid in a part of the layer 2 near the injection well 16 (which is at a greater depth) before extraction of fluid from the reservoir will be at a higher temperature than the fluid in a part of the layer 2 near the production well 20 (which is at a shallower depth).

As fluid is extracted from the reservoir, the fluid within the reservoir rock will flow within the reservoir away from the injection well and towards the production well (ie along layers 2 and 4 shown in Figure 1). While there will be some heat transfer between the fluid flowing within the reservoir to the surrounding rock, the magnitude of this heat transfer is relatively small.

Therefore, for any two portions of fluid flowing into the reservoir at different times, a difference in the temperature of the portions of fluid will be caused by a difference in the initial temperature of the portions of fluid, which in turn will have been caused by differences in the geothermal temperature at the source locations for the two portions of fluid. A difference in depth for the source positions of the two portions of fluid can therefore be determined from the difference in temperature.

As the fluid flows into the production well, the distance between the two positions along the flow direction of the fluid within the layer can also be determined from the flow rate of fluid into the reservoir. For the two portions of fluid, a separation distance can therefore be determined from the amount of fluid flowing into the well during the period between the first portion of fluid flowing into the well and the second portion flowing into the well.

The reservoir will typically have a relatively continuous flow of fluid, and the temperature will therefore change gradually as the fluid enters the well. Instead of considering only two discrete portions of fluid, the flow rate of the fluid into the reservoir, and the rate of change over time in the temperature of the fluid entering the production well over time, can therefore be used to determine an estimate of the slope, i.e. the change in depth by distance. By identifying a flow rate for fluid, a velocity for the fluid through the reservoir layer can be determined. This speed is indicative of the distance that a given portion of fluid has traveled along the layer in the direction of flow of fluid within the layer during a given time.

Figure 6 shows an example of graphical output showing temperature versus time for fluid entering a production well, such as production well 20 shown in Figure 1. As can be seen, the temperature of the fluid gradually increases from approximately 71 °C to 72 °C in during approximately 2,500 days (this temperature change and time period is only an example). The change in temperature has a trend, shown at line 71.

As described above, this is indicative of fluid entering the well in the early part of the reservoir's lifetime (ie from day 0), and which originates at a depth corresponding to a geothermal temperature of approximately 71 °C. In the later part of the reservoir's lifetime (ie around day 2500), this is indicative of the fluid originating at a depth corresponding to a geothermal temperature of approximately 72 °C.

Some further examples of the application of temperature data to estimate the slope of a reservoir will now be described, initially in brief form.

According to a first example, there is provided a computer-implemented method for estimating a slope of a layer in a reservoir, it being a production well that runs into the layer of the reservoir, arranged so that fluid flows from the layer into the production well, the production well further comprising one or several devices that are arranged to measure a temperature of fluid at one or more locations within the production well at a plurality of times, the method comprising: receiving temperature data from the one or more devices, the temperature data being indicative of a temperature of fluid that comes into the production well from the formation at each of a plurality of points during a period of time; identifying, using the temperature data, a trend indicative of a change in temperature of the fluid entering the production well during the time period; identifying a velocity of fluid within the bed in a flow direction of fluid within the bed during the time period; determining, using the identified trend and the identified velocity, an estimate of the change in temperature by distance for the fluid, the distance being in a direction of flow of fluid within the layer; identify a geothermal gradient indicative of a change with depth in the temperature of rock within and around the reservoir; and determining a measure of the slope of a layer in the reservoir based on the predicted change in temperature with distance and the geothermal gradient.

The temperature of the fluid entering the well can change over time. By monitoring the temperature, and thus the flow rates, such changes in temperature can be identified. These temperature changes can be used to determine information about the reservoir. The slope of the reservoir can, for example, be determined from the development of the fluid temperature over time. The "slope" of the reservoir indicates that the depth of the reservoir is not constant. The temperature development is therefore caused by fluid that is carried along the reservoir from a deeper or shallower point. The development can take many days, and perhaps years, as it takes time for the fluid to flow to the inflow point. The slope of the reservoir can therefore be determined from the change in temperature, and the modeling and mapping of the reservoir can thus be improved.

In some examples, the trend may be determined over a period longer than one month. In some examples, the method may comprise identifying a flow rate of fluid into the production well from the formation whereby the velocity of fluid within the formation is estimated. In some examples, the method may include: identifying a height of a permeable layer containing the fluid within the reservoir, whereby the velocity of fluid within the layer is estimated.

In some examples, the method may comprise multiplying the flow rate by a predetermined constant, whereby the flow rate is estimated, the predetermined constant being calculated depending on the arrangement of at least one injection well in connection with the production well.

The flow rate of fluid within the reservoir, or the flow rate of fluid entering the production well and the size of the associated layer in the reservoir (specifically height), can be used to link the change in temperature over time to a change in temperature over distance. In many cases, the flow of fluid is not linear, as the fluid will enter the well from an arc (or full circle) that surrounds the well. A predetermined constant can thus be used to link the inflow rate and height to a velocity of fluid within the reservoir.

In some examples, the method may include associating a change in temperature of the fluid entering the production well with a change in depth based on the reservoir's geothermal gradient whereby a measure of the layer's slope is determined. By applying the geothermal gradient, the change in temperature along length can be used to determine a change in depth along length, i.e. the slope of the reservoir.

According to another example, a computer-readable storage medium is provided which stores computer-readable instructions thereon for execution on a computer system to implement a method of estimating a slope in a reservoir bed, being a production well running into the reservoir bed, arranged so that fluid flows from the layer into the production well, the production well further comprising one or more devices arranged to measure a temperature of fluid at one or more locations within the production well at a plurality of times, the instruction set being arranged to cause the data processing system to perform the steps of: receiving temperature data from the one or more devices, the temperature data being indicative of a temperature of fluid entering the production well from the formation at each of a plurality of points during a time period; identifying, using the temperature data, a trend indicative of a change in temperature of the fluid entering the production well during the time period; identifying a velocity of fluid within the bed in a flow direction of fluid within the bed during the time period; determining, using the identified trend and the identified velocity, an estimate of the change in temperature by distance for the fluid, the distance being in a direction of flow of fluid within the layer; identify a geothermal gradient indicative of a change with depth in the temperature of rock within and around the reservoir; and determining a measure of the slope of a layer in the reservoir based on the predicted change in temperature with distance and the geothermal gradient.

According to a third example, a system is provided for estimating a slope in a layer in a reservoir, there being a production well that runs into the layer in the reservoir, arranged so that fluid flows from the layer into the production well, the production well further comprising one or several devices that are arranged to measure a temperature of fluid at one or more locations within the production well at a plurality of times, the system comprising: a boundary layer that is arranged to receive temperature data, the temperature data being collected by the one or more devices , the temperature data being indicative of a temperature of fluid entering the production well from the formation at each of a plurality of points during a time period; and a processor arranged to: identify, using the temperature data, a trend indicative of a change in temperature of the fluid entering the production well during the time period; identifying a velocity of fluid within the bed in a flow direction of fluid within the bed during the time period; determining, using the identified trend and the identified velocity, an estimate of the change in temperature by distance for the fluid, the distance being in a direction of flow of fluid within the layer; identify a geothermal gradient indicative of a change with depth in the temperature of rock within and around the reservoir; and determining a measure of the slope of a layer in the reservoir based on the predicted change in temperature with distance and the geothermal gradient.

A method of estimating the slope in a reservoir from a trend in the temperature of the fluid entering a production well from a reservoir, which can be performed by computer system 200, will now be described below with reference to Figure 7.

In step 72, and according to the instruction set defined by the FE software components 209, the processor 204 receives temperature data from the DTS 36 for a plurality of times. This can, for example, be over the course of many days. Temperature data is typically collected for a longer period than a month and can be collected for periods that have a duration of more than a year. The DTS data can identify the temperature of the fluid within the annulus 22, as described above in Figure 3, as direct measurement of the temperature of the fluid before it enters the annulus (ie with a DTS integrated in the reservoir) can alternatively be performed. The temperature data can be connected to only a single inflow point as described above in figures 2 and 3, the temperature data in some examples, however, can be connected to several inflow points.

In step 74, the processor 204 identifies from the DTS data the temperature of the fluid in the reservoir before the fluid enters the annulus at each time. This can be done by analyzing the temperature of the fluid in the annulus to determine the temperature of the fluid in the reservoir at its source position before the fluid flows through the reservoir layer and enters the annulus, using, for example, the models described above. In the alternative, other methods (such as by using direct measurement of the temperature of the fluid in the reservoir before the fluid enters the annulus) can, however, be used. In this step, the processor 204 can identify the temperature of the fluid in the reservoir entering the annulus at only a single inflow point as described above in Figures 2 and 3. The processor 204 can alternatively determine temperatures for several inflow points and calculate the average of these temperatures. As shown in Figure 1, a reservoir can comprise several layers; the processor 204 can therefore calculate the average for the temperature of the fluid for a single, or for each, layer.

In step 76, the processor 204 identifies a possible trend in the temperature data. This trend can be over many days and typically over longer periods than a month. An example of such a trend is shown in figure 6. The processor 204 also identifies the flow rate of fluid from the reservoir layer into the production well during this period. This flow rate can be determined by the processor 204 for example according to embodiments described above or can be received by the processor 204 from a further device, such as a flow rate sensor connected to the production well.

In step 78, the processor 204 calculates an estimate of the slope in the reservoir from the identified trend. The slope can be calculated using an equation such as:

where:

dT

— is the change in temperature over time (ie, the trend identified in step 76);

date

A is a factor calculated based on the arrangement of the injection and production wells;

Q is the flow rate of fluid from the formation into the production well identified by the processor in step 76;

H is the depth in the layer (at the production well), which can be determined by methods known in the art from, for example, survey data;

L is the inter-well distance that can be determined from the known locations in the injection and production wells; and

—— is the temperature change in the fluid in the direction of the well pair.

dx

A Q/ H together represents an indication of the velocity of the fluid within the reservoir in the direction of flow of fluid within the reservoir.

After the temperature change in the fluid in the direction of the well pair has been calculated, the reservoir slope can then be calculated by assuming that the fluid was originally at, or close to, the geothermal temperature, and comparing the geothermal temperature at known depths with the temperature change in the direction of the well pair. The geothermal temperature can be determined using techniques known in the art from, for example, survey data.

The factor A can be determined from the arrangement of the wells in the reservoir. One such arrangement will be described with reference to figure 8.1 figure 8 is a series of production wells arranged approximately in line with each other, as represented by wells 80A, 80B and 80C. At a distance from, and parallel to, these production wells 80A, 80B and 80C are the injection wells 82A, 82B and 82C.

The injection and production wells are arranged in respective lines roughly perpendicular to a gradient of the underlying reservoir. The gradient of the reservoir is represented by the lines 84 (representing the contours of the reservoir).

As represented by the lines 86, the flow between the wells does not always follow the direct path (ie the line with the least distance between the injection well and the production well) between the injection and production wells, and the path length between the relevant wells can thus vary. By using methods known in the art to calculate mean path length and the like, the factor A can consequently be derived based on the location of the injection and production wages. In this case, the factor A can have a value of 0.065.

While in the above example it is assumed that the temperature of the fluid increases over time, this is not necessarily the case; in other examples, the temperature can decrease, e.g. in case the reservoir decreases in depth towards the production well.

It shall be understood that any feature described in connection with any embodiment may be used alone, or in combination with, other described features, and may also be used in combination with one or more features of any other of the embodiments, or any combination of any other of the embodiments. Equivalents and modifications not described above can also be used without deviating from the scope of the accompanying requirements. The features according to the requirements can be combined in other combinations than those specified in the requirements.

Claims (28)

1. Computer-implemented method for estimating flow of fluid into a production well running into a reservoir comprising fluid, the well comprising a central pipe and an annulus surrounding the central pipe, the annulus being connected to the reservoir to receive fluid at a or several inflow points, and the central pipe has at least one inlet, arranged to allow fluid to flow from the annulus into the central pipe, and is placed downstream of the one or more inflow points, the production well further comprising one or more devices which are arranged to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the method comprising: receiving temperature data from the one or more devices, which are indicative of a temperature of fluid at a plurality of points along the length of the annulus; identifying a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; applying a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being arranged so that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition. 2. The method according to claim 1, comprising using the model to determine a specific heat capacity for the fluid and thereby estimate a composition of the fluid flowing from the reservoir into the annulus at the first inflow point. 3. The method according to any one of the preceding claims, comprising: using the model to estimate a rate at which the fluid flows along the longitudinal axis of the annulus, thereby estimating a rate at which fluid flows into the annulus at the first inflow location. 4. The method according to any one of the preceding claims, comprising: identifying a temperature of fluid within the central tube; and determining a temperature gradient between the fluid within the central tube and the fluid within the annulus, whereby heat transfer from the central tube to fluid flowing within the annulus is estimated. 5. The method according to any one of the preceding claims, comprising: identifying a change in temperature of fluid within the annulus between a point upstream of the first inflow point and a point downstream of the first inflow point; applying a further model to estimate a change in temperature of the fluid in the annulus caused by fluid entering the annulus from the reservoir at the first inflow location; and estimating a rate at which fluid flows into the annulus at the first inflow location, based on the identified change in temperature and the predicted change in temperature, 6. The method according to claim 5, comprising: identifying a geothermal temperature at a depth corresponding to the first inflow location, whereby a temperature of fluid flowing into the annulus at the first inflow location is estimated, wherein the further model is configured to estimate the change in temperature of the fluid in the annulus based on the temperature of the fluid entering the annulus at the inflow point. 7. The method according to claim 5 or claim 6, in which the further model is arranged so that fluid flowing within the annulus is assumed to be mixed with fluid entering the annulus at the first inflow point, and connecting the change in temperature of the fluid within the annulus with a flow rate and a temperature of fluid flowing within the annulus upstream of the first inflow location, and a flow rate and a temperature of fluid flowing into the annulus at the first inflow location. 8. The method according to any one of claims 5 to 7, comprising using a still further model to estimate a change in temperature of fluid flowing into the annulus at the first inflow location, the still further model taking into account Joule-Thompson -expansion of fluid flowing into the annulus at the first inflow point. 9. The method according to any one of the preceding claims, comprising using said model to refine an estimate of a rate at which fluid flows into the annulus at the first inflow location generated by a further said model. 10. The method according to any one of the preceding claims, comprising using a mentioned model and/or a mentioned further model whereby a rate at which fluid flows into the annulus at one or more other inflow points is estimated. 11. The method according to claim 10, comprising using the model and/or the further applied model to estimate a rate at which fluid flows into the annulus at one or more other inflow points whereby the estimate of the rate at which fluid flows into the annulus at the first the point of inflow, is refined. 12. The method according to any one of the preceding claims, comprising: estimating a set of values for rates at which fluid flows into the annulus at the first inflow location, each value being associated with data indicative of a composition of the fluid which flows into the annulus at the first inflow point. 13. The method according to any one of the preceding claims, wherein the annulus is divided into a plurality of sections, each section having one or more inflow points, and the central tube having an inlet open to the annulus and located at the downstream end of each section , the method comprising: estimating flow rates of fluid from the reservoir into a first mentioned section; estimating a flow rate of fluid from the first section into the central tube through a first said inlet from the flow rates of fluid from the reservoir into the first section; estimating a flow rate of fluid within the central tube downstream of the first section based on the estimated flow rate of the fluid through the first inlet of the first section; and estimating flow rates of fluid within a second said section using the estimated flow rate of fluid within the central tube. 14. The method according to any one of the preceding claims, comprising receiving data indicative of, or one or more of, measurements of the temperature, composition and flow rate of fluid in the central tube, and using the measurement data to validate data generated by the models . 15. The method according to any one of the preceding claims, comprising: receiving temperature data for fluid flowing into the annulus at the first inflow location at a plurality of times; and identifying a change over time in a temperature of the fluid flowing into the annulus at the first inflow location. 16. The method according to claim 15, comprising: identifying a flow rate of fluid entering the production well at the first inflow location at each of the plurality of times; identify a geothermal gradient indicative of a change with depth in temperature of rock within and around the reservoir; and determining a measure of the slope in a layer of the reservoir based on the change over time in the temperature, the geothermal gradient and the flow rate. 17. Computer-readable storage medium storing computer-readable instructions thereon for execution on a data processing system for implementing a method of estimating flow of fluid into a production well running into a reservoir comprising fluid, the well comprising a central pipe and an annulus surrounding it the central tube, the annulus being connected to the reservoir to receive fluid at one or more inflow points, and the central tube having at least one inlet, arranged to allow fluid to flow from the annulus into the central tube, and being located downstream of the one or the several inflow points, the production well further comprising one or more devices which are arranged to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the instruction set being arranged to cause the data processing system to perform the steps of: receiving temperature data from the one or more devices indicative of a temperature of fluid at a plurality of points along the length of the annulus; identifying a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; applying a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being arranged so that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition. 18. The computer-readable storage medium according to claim 17, wherein the instruction set is arranged to cause the data processing system to apply the model to determine a specific heat capacity for the fluid and thereby estimate a composition of the fluid flowing from the reservoir into the annulus at the first inflow location. 19. The computer-readable storage medium according to claim 17 or claim 18, wherein the instruction set is arranged to cause the data processing system to: apply the model to estimate a rate at which the fluid flows along the longitudinal axis of the annulus, thereby estimating a rate at which fluid flows into the annulus at the first inflow point. 20. The computer-readable storage medium according to any one of claims 17 to 19, wherein the instruction set is arranged to cause the data processing system to: identify a change in temperature of fluid within the annulus between a point upstream of the first inflow site and a point downstream of the first the site of inflow; applying a further model to estimate a change in temperature of the fluid in the annulus caused by fluid entering the annulus from the reservoir at the first inflow location; and estimating a rate at which fluid flows into the annulus at the first inflow location, based on the identified change in temperature and the predicted change in temperature. 21. The computer-readable storage medium of claim 20, wherein the instruction set is arranged to cause the data processing system to: identify a geothermal temperature at a depth corresponding to the first inflow location, whereby a temperature of fluid flowing into the annulus at the first inflow location is estimated, wherein the further model is adapted to estimate the change in temperature of the fluid in the annulus based on the temperature of the fluid entering the annulus at the point of inflow. 22. The computer-readable storage medium according to claim 20 or claim 21, in which the further model is arranged so that fluid flowing within the annulus is assumed to be mixed with fluid entering the annulus at the first inflow point, connecting the change in temperature of the fluid within the annulus with a flow rate and a temperature of fluid flowing within the annulus upstream of the first inflow point, and a flow rate and a temperature of fluid flowing into the annulus at the first inflow point. 23. System for estimating flow of fluid into a production well running into a reservoir comprising fluid, the well comprising a central tube and an annulus surrounding the central tube, the annulus being connected to the reservoir to receive fluid at one or several inflow points, and the central pipe has at least one inlet, arranged to allow fluid to flow from the annulus into the central pipe, and is placed downstream of the one or more inflow points, the production well further comprising one or more devices which are arranged for to measure a temperature of fluid within the annulus at a plurality of points along the length of the annulus, the system comprising: an interface arranged to receive temperature data, the temperature data having been collected by the one or more devices and being indicative of a temperature of fluid at a plurality of points along the length of the annulus; and a processor arranged to: identify a change in temperature of fluid flowing within the annulus, based on the received temperature data at the plurality of points; run a model to estimate heat transfer from the central tube to fluid flowing within the annulus, the model being configured such that the heat transfer is assumed to be substantially constant along the length of the tube; and estimating a rate at which fluid flows into the annulus from the reservoir at a first inflow location, based on the identified change in temperature between the points and the estimated heat transition. 24. The system according to claim 23, wherein the processor is arranged to use the model to determine a specific heat capacity for the fluid and thereby estimate a composition of the fluid flowing from the reservoir into the annulus at the first inflow point. 25. The system according to claim 23 or claim 24, wherein the processor is arranged to use the model to estimate a rate at which the fluid flows along the longitudinal axis of the annulus, thereby estimating a rate at which fluid flows into the annulus at the first inflow point. 26. The system according to any one of claims 23 to 25, wherein the processor is arranged to: identify a change in temperature of fluid within the annulus between a point upstream of the first inflow location and a point downstream of the first inflow location; running a further model to estimate a change in temperature of the fluid in the annulus caused by fluid entering the annulus from the reservoir at the first inflow location; and estimating a rate at which fluid flows into the annulus at the first inflow location, based on the identified change in temperature and the predicted change in temperature. 27. The system according to claim 26, wherein the processor is arranged to: identify a geothermal temperature at a depth corresponding to the first inflow location, whereby a temperature of fluid flowing into the annulus at the first inflow location is estimated, wherein the additional model is configured to to estimate the change in temperature of the fluid in the annulus based on the temperature of the fluid entering the annulus at the inflow point. 28. The system according to claim 26 or claim 27, in which the further model is arranged so that fluid flowing within the annulus is assumed to be mixed with fluid entering the annulus at the first inflow point, and connecting the change in temperature of the fluid within the annulus with a flow rate and a temperature of fluid flowing within the annulus upstream of the first inflow location, and a flow rate and a temperature of fluid flowing into the annulus at the first inflow location.