WO2014148925A1

WO2014148925A1 - Method and system for monitoring and/or controlling fracture connectivity

Info

Publication number: WO2014148925A1
Application number: PCT/NZ2014/000050
Authority: WO
Inventors: Peter LEARY
Original assignee: Auckland Uniservices Limted
Priority date: 2013-03-22
Filing date: 2014-03-24
Publication date: 2014-09-25

Abstract

Method and system for determining or predicting a parameter (alpha) indicative of fracture connectivity from core sample information either before or after injection of pressurised fluid to induce fracturing in a geological or geothermal reservoir or other subsurface region. Alpha and/or changes in alpha are monitored during fluid pressurisation through wellbore to control pressurisation, preferably to acquire a desired degree of fracture connectivity for improving reservoir productivity and performance.

Description

"METHOD AND SYSTEM FOR MONITORING AND/OR CONTROLLING

FRACTURE CONNECTIVITY"

FIELD OF INVENTION

The invention comprises a method and system for monitoring, analysing and/ or controlling permeability in a geothermal or hydrocarbon reservoir.

BACKGROUND

Production efficiency of a geothermal or hydrocarbon wellbore accessing the geothermal or hydrocarbon reservoir is related to the degree of permeability or fracture connectivity in the geological formations such as rock comprising the reservoir. Thus zones of rock with good permeability may be productive zones for drilling and resource extraction.

SUMMARY OF INVENTION

It is an object of the invention to provide an improved or at least alternative method and/ or system for monitoring, analysing or controlling fracture connectivity and/ or permeability.

In a first aspect the invention may broadly be said to consist of a method for monitoring fracture connectivity in a geothermal or hydrocarbon reservoir comprising the steps of:

assessing one or more physical parameters of rock volume within a reservoir in situ, determining or predicting a parameter indicative of fracture connectivity (hereinafter: alpha), and

determining a change in alpha over time to monitor change in fracture connectivity within the reservoir.

Preferably the step of determining or predicting alpha comprises or the step of determining a change in alpha or both comprises determining or predicting alpha empirically from rock volume porosity and rock volume permeability.

Preferably assessing one or more physical parameters of rock volume comprises assessing one to N samples (where N is equal to or greater than 1) of well-core permeability values, κ„, and well- core porosity values, φ„. Preferably determining or predicting alpha comprises deterrriining from the measured parameters the ratio of a standard deviation of the logarithm of the well-core permeability values, logn,,, and a standard deviation of well-core porosity values, φ„:

α≡ %_</σ_φ.

Preferably the method further comprises after determining or predicting alpha pressurising a fluid through a well-bore associated with the geothermal or hydrocarbon reservoir, and the step of determining a change in alpha over time comprises determining a change in alpha over time to monitor changes in fracture connectivity within the reservoir surrounding the well-bore due to the induction of pressurised fluid.

In one embodiment determining the change in alpha comprises measuring and/or monitoring seismic events induced by the step of pressurising the fluid through the well-bore. Preferably determining the change in alpha further comprises determining spatial statistics of relative locations for a population of seismic events induced by well-bore pressurization.

Preferably the spatial statistics are determined using a 'two-point correlation function' (TPCF), T(r) —\f (x) flx+ή (f x where f (x) is a damage density at point x in the medium, and r is an arbitrary scale distance.

Preferably determining the change in alpha further comprises determining an exponent variable, p, from the following equation:

T(r) ~ l/r^p.

In a second aspect the invention may broadly be said to consist of a method for controlling fracture connectivity in a crustal rock volume of a geothermal or hydrocarbon reservoir comprising the steps of:

pressurising a fluid through a well-bore associated with the geothermal or hydrocarbon reservoir, and

determining a change in a parameter indicative of fracture connectivity (hereinafter: alpha) in response to wellbore fluid pressurisation to monitor, validate or measure change in fracture connectivity due to wellbore fluid pressurisation. Preferably determining the change in alpha is performed during or after the step of pressurising the reservoir fluid through the well-bore.

Preferably determining the change in alpha comprises measuring and/or monitoring seismic events induced by the step of pressurising the reservoir fluid through the well-bore.

Preferably determining the change in alpha further comprises determining spatial statistics of relative locations for a population of seismic events induced by well-bore fluid pressurization. Preferably the spatial statistics are determined using a 'two-point correlation function' (TPCF), T(r) =\f (x) flx+ή f x where / (x) is a damage density at point x in the medium, and r is an arbitrary scale distance within the volume.

T(r) ~

Preferably the method further comprises prior to pressurising the fluid through the well-bore, assessing one or more physical parameters of the crustal rock volume in situ to determine or predict an initial value of alpha.

Preferably the step of determining or predicting alpha comprises determining or predicting alpha empirically from rock volume porosity and rock volume permeability. Preferably wherein assessing one or more physical parameters of rock volume comprises assessing one to N samples (where N is equal to or greater than 1) of well-core permeability values, κ,„ and well-core porosity values, φ_Λ.

Preferably determining or predicting alpha comprises determining from the measured parameters the ratio of a standard deviation of the logarithm of the well-core permeability values, /¾κ„, and a standard deviation of well-core porosity values, φ„: Preferably the method further comprises the step of determining pressurisation data based on the change in alpha for controlling pressurisation of a fluid through a wellbore associated with the reservoir. In a third aspect the invention may broadly be said to consist of a method for determining pressurization of a well-bore in a geothermal or hydrocarbon reservoir comprising the steps of: determining a change in the parameter indicative of fracture connectivity (hereinafter: alpha), and

generating pressurisation data according to the change in alpha for controlling pressurization of the well-bore.

Preferably the method further comprises during or after or both during and after determining the change in alpha, pressurising a fluid through a well-bore associated with the geothermal or hydrocarbon reservoir in accordance with the pressurisation data.

Preferably the step of generating reservoir pressurisation data comprises comparing the determined change in alpha with a desired value of alpha or a desired value of change in alpha, and generating reservoir pressurisation data based on the comparison to achieve the desired alpha or the desired change in alpha.

Preferably the method further comprises before determining the change in alpha, pressurising a fluid through a well-bore associated with the geothermal or hydrocarbon reservoir.

Preferably the method further comprises prior to determining the change in alpha, assessing one or more physical parameters of the crustai rock volume in situ to determine or predict alpha.

Preferably the step of determining or predicting alpha comprises determining or predicting alpha empirically from rock volume porosity and rock volume permeability. Preferably assessing one or more physical parameters of rock volume comprises assessing one to N samples (where N is equal to or greater than 1) of well-core permeability values, κ,„ and well- core porosity values, φ„. Preferably determining or predicting alpha comprises determining from the measured parameters the ratio of a standard deviation of the logarithm of the well-core permeability values, ¾κ„, and a standard deviation of well-core porosity values, φ„:

Preferably determining the change in alpha comprises measuring and/ or monitoring seismic events induced by the step of pressurising the fluid through the well-bore.

Preferably deternining the change in alpha further comprises detemaining spatial statistics of relative locations for a population of seismic events induced by well-bore pressurization.

Preferably the spatial statistics are determined using a 'two-point correlation function' (TPCF), T(T) —\f (x) ft +ή cf x where (x) is a damage density at point x in the medium, and r is an arbitrary scale distance.

Τ(ή = l/r^p. In a fourth aspect the invention may broadly be said to consist of a method for monitoring permeability in a geothermal or hydrocarbon reservoir comprising the steps of:

determining a change in alpha over time to monitor fracture connectivity within the reservoir.

In a fifth aspect the invention may broadly be said to consist of a method for controlling permeability in a crustal rock volume of a geothermal of hydrocarbon reservoir comprising the steps of:

determining a change in a parameter indicative of fracture connectivity (hereinafter: alpha) in response to pressurisation to validate change in fracture connectivity due to pressurisation. In a sixth aspect the invention may broadly be said to consist of a method for determining pressurization of a well-bore in a geothermal or hydrocarbon reservoir comprising the steps of: determining a change in a parameter indicative of fracture connectivity (hereinafter: alpha), and

generating pressurisation data according to the change in alpha for pressurization of the well-bore.

In a seventh aspect the invention may broadly be said to consist of a system for monitoring or controlling fracture connectivity in a geothermal or hydrocarbon reservoir, the system comprising:

a memory component configured to store data indicative of a parameter relating to fracture connectivity in the reservoir (hereinafter: alpha), and

a processing component configured to:

determine a change in alpha based on one or more measured parameters during or after pressurisation of a well-bore associated with the reservoir.

Preferably the processor is further configured to generate pressurisation data according to the change in alpha for pressurisation of the well-bore.

Preferably the system further comprises a fluid injection machine configured to pressurise a wellbore associated with the reservoir to induce fracturing.

Preferably the processor is configured to generate pressurisation data according to the change in alpha and the fluid injection machine is configured to pressurise the wellbore in accordance with the pressurisation data.

Preferably the processor is configured to receive data indicative of seismic events induced by pressurising of fluid through a well-bore associated with the reservoir and determine the change in alpha using the received seismic event data.

Preferably the processor is configured to determine the change in alpha by determining spatial statistics of relative locations for a population of seismic events induced by well-bore pressurization. Preferably the processor is configured to determine spatial statistics using a 'two-point correlation function' (TPCF), T(f)—\j (x) flx+ή fx where f (x) is a damage density at point x in the medium, and ris an arbitrary scale distance within the volume.

Preferably the processor is configured to detemiine the change in alpha by determining an exponent variable, p, according to the following equation:

T(r) ~ l/r^p.

Preferably the system further comprises a plurality of seismic sensors configured to obtain data indicative of seismic events induced by pressurisation.

Preferably the processor is further configured to assess one or more physical parameters of the crustal rock volume in situ to determine or predict an initial value of alpha and store the initial value of alpha in the memory component.

Preferably the processor is configured to receive data indicative of rock volume porosity and data indicative of rock volume permeability and determine or predict alpha empirically from the rock volume porosity data and the rock volume permeability data.

Preferably the processor is configured to assess one or more physical parameters of rock volume by assessing one to N samples (where N is equal to or greater than 1) of well-core permeability values, κ, and well-core porosity values, φ„.

Preferably the processor is configured to determine or predict alpha by determining from the physical parameters the ratio of a standard deviation of the logarithm of the well-core permeability values, /¾κ„ and a standard deviation of well-core porosity values, φ„:

In an eighth aspect the invention m )' broadly be said to consist of a method for determining pressurization of a well-bore in a geothermal or hydrocarbon reservoir comprising the steps of: assessing one or more physical parameters of the crustal rock volume in situ to determine or predict a parameter indicative of fracture connectivity in the rock medium surrounding the wellbore,

determining a change in the parameter indicative of fracture connectivity, and utilising the change in the parameter to determine the spatial extent of pressurization activity beyond the well-bore . Any one or more of the above embodiments or preferred features can be combined with any one or more of the above aspects.

In a geological formation such as rock, a fracture is conventionally considered as any local separation or discontinuity plane, such as a joint or a fault that mechanically divides the rock into two or more pieces, and are typically thought of as extending fissures or crevices in the rock, such as fractures caused by tectonics -induced tensile stress exceeding the rock strength causing the rock to lose cohesion along its weakest plane.

In accordance with the invention, production efficiency of a geothermal or hydrocarbon well is increased by increasing the degree of fracture interconnectedness or connectivity throughout the rock in all directions, and/or between areas of relatively high fracture interconnectedness localised around separated defect sites in the rock, by increasing or maximising connected breakdown of cement bonds (typically calcite or silica) between harder rock particles or aggregates of particles of the rock, increasing bulk permeability through the rock. This is achieved by pressurising a fluid (liquid or gas) through the well-bore under pressure controlled to achieve or approach a desired degree of such fracture interconnectedness or connectivity.

The invention may be useful in relation to drilling and fluid extraction from geothermal and/ or hydrocarbon reservoirs.

The term "comprising" as used in this specification and claims means "consisting at least in part of. When interpreting each statement in this specification and claims that includes the term "comprising", features other than that or those prefaced by the term may also be present. Related terms such as "comprise" and "comprises" are to be interpreted in the same manner. BRIEF DESCRIPTION OF THE FIGURES

In the accompanying figures which are referred to in the following description of experimental work:

Figure 1 is a block diagram of a preferred form fracture monitoring/control system of the invention,

Figure 2 is a flow diagram of a preferred form method for fracture monitoring/ control utilising the system of figure 1,

Figure 3 is a graph showing normalised fluctuations of φ„ and /<¾κ_η measured experimentally at increasing depths down a well-bore,

Figure 4a shows magnitude grading of flow velocities for a fluid moving from a source well to a sink well in an essentially uniformly permeable medium,

Figure 4b magnitude grading of flow velocities for a fluid moving from a source well to a sink well in an essentially non-uniformly permeable medium where permeability is controlled by fracture connectivity,

Figure 5 shows a quantitative representation of control of fluid flow velocity distributions by arameter a, and

Figure 6 is a graph showing variation of a power -law exponent p for two cases of fracture connectivity parameter a (green/red lines denote numerical results of simulated failure events in a fracture -permeable medium; black lines are regression curves determining the slop of the power - law scaling simulation data) .

DETAILED DESCRIPTION OF EMBODIMENTS

The invention relates to a system and method for monitoring, analysing and/or controlling fracture connectivity within a geothermal reservoir. The method or system designates and determines a rock physical parameter, hereinafter referred to as alpha, a, for convenience. The parameter, α , provides a measure for analysing/ controlling the degree to which naturally occurring fractures in a crustal rock volume are interconnected to form fluid percolation pathways allowing fluids to pass through the volume. An increase in the value of parameter a within a given crustal volume is indicative of an increase in the degree to which naturally occurring percolation pathway fractures are connected within the volume, and hence the degree to which fluids can pass through the volume for a given differential pressure impressed across the volume. Any physical process conducted within the crustal volume that increases the value of parameter a is indicative of an increase in the fracture permeability/ connectivity of the volume. In the following description, specific details are given to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, software modules, functions, circuits, etc., may be shown in block diagrams in order not to obscure the embodiments in unnecessary detail. In other instances, well-known modules, structures and techniques may not be shown in detail in order not to obscure the embodiments.

Also, it is noted that the embodiments may be described as a process that is depicted as a flowchart, a flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be rearranged. A process is terminated when its operations are completed. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc., in a computer program. When a process corresponds to a function, its termination corresponds to a return of the function to the calling function or a main function. Aspects of the systems and methods described below may be operable on any type of general purpose computer system or computing device, including, but not limited to, a desktop, laptop, notebook, tablet or mobile device.

Referring to figure 1 a diagram of a system 100 for controlling, monitoring and/or analysing fracture connectivity and/ or permeability of a subsurface region or crustal rock volume, and in particular a geological or geothermal reservoir 170 is shown. The invention could also be used in hydrocarbon or other type reservoirs. The system 100 includes equipment or machinery 150 for inducing fracturing through a wellbore 190 associated with the reservoir 170. In the preferred embodiment, a fluid (liquid or gas) injection machine 150 is provided for injecting pressurised fluid down a wellbore 1 0 of the reservoir 170 and inducing fracturing to increase permeability of the crustal rock volume in the reservoir 170. The injected fluid may be pressurised liquid (such as water or other liquid) or gas (such as the product of propellants), such as for example pressurised water. One or more data gathering sources 110 configured to obtain geological data indicative of one or more parameters associated with the behaviour of the rock volume (preferably in response to pressurisation) are also provided.

The fluid injection machine 150 and the data gathering sources 110 are communicatively coupled to an electronic control and/or analysis system 115 configured to monitor and/ or analyse fracture connectivity behaviour during pressurisation. The control system 115 is preferably further configured to output pressurisation data for conttolling the fluid injection machine 150 based on the degree of fracture connectivity and other predetermined criteria (such as desired or maximum level of fracture connectivity). The control system 115 comprises a memory component 120 configured to store information 125 communicated to the control system from the data gathering sources 110 and configured to store information relating to the methodology for determining one or more parameters indicative of fracture connectivity and/or for deterrnining one or more parameters for controlling pressurisation (such as empirical formulas and algorithms). The control system further comprises a processing component 130 configured to process the data gathered 125 by the data gathering source 110, in accordance with the algorithms, formulas or other methods stored in memory 120, to at least determine or predict one or more parameters indicative of the degree of fracture connectivity (either before, during or after pressurisation or any combination thereof) . In the preferred embodiment, the processing component 130 is further configured to determine pressurisation data or one or more parameters for controlling the fluid injection machine 150 based on the parameters indicative of fracture connectivity.

An output interface 140 may be communicatively coupled to the control system 115 for communicating data output from the processing component, indicative of the degree of fracture connectivity and/ or pressurisation data for example, to a user and/ or machine 110 to control the machine 110 according to a degree of fracture connectivity and/or according to a desired degree of fracture connectivity.

The system 100 may further comprise any combination of drilling equipment for drilling one or more wellbores for fluid injection, and/ or extraction equipment for extracting resources through any of the wellbores. Resources may include natural gas, oil, hot water and/ or minerals.

The various components of the system 100 may be communicatively coupled direcdy to one another and/ or via a communications network 160.

Empirical definition of parameter a

In the preferred embodiment of the invention, the parameter a is formally defined via an empirical relation between rock volume porosity and rock volume permeability. To analyse this parameter experimentally, N core samples numbered // = 1 N can be taken from a well-bore cored through a rock volume. Standard laboratory measurements on the ; "*""^*" core sample return a value of core porosity φ„ and core permeability κ_/;. Well core permeability values κ„ are converted to the logarithm of the well core permeability value, /<¾κ„. The statistical mean and standard deviation from the mean are computed from the two sequences φ„ and /¾κ_η:

(i) _Φ = 1/Ν∑φ,

(iii) a, = [l/N∑(¾ - $)

(iv) σ_¾ = [1/Ν Σ( „- ½_ί)²]^1/2

In the preferred embodiment, parameter a for the crustal volume, from which the well core data is taken, is then defined as the ratio of the standard deviation of well-core sequence /¾κ_;, to the standard deviation of well-core sequence φ,„

The above means that fluctuations of φ„ and logi_n are closely related by this parameter, a. In other words: logA. - bgi ~ α(φ„-¾)·

Figure 3 shows a graph of normalised fluctuation of φ„ and /<¾κ_η measured experimentally at increasing depths down a well-bore. The graph validates the close (proportional) relationship between these fluctuations which can be represented through an empirically determined parameter, a. Permeability as function of porosity under control of parameter a

The empirical definition of parameter a is equivalent to a sample-by-sample relationship between well-core /^permeability) hgx._n and well-core porosity φ,„

Re-expressing this relation explicitly gives sample permeability κ„ in terms of sample // porosity φ_;, and parameter a, κ„ = κ ^[α(φ„- (β)].

Parameter a is thus seen to control the physical relationslup between porosity and permeability distributions in a crustal volume. For a fixed porosity distribution, the permeability distribution depends on the value of parameter a. For a fixed porosity distribution, increases in parameter a are equivalent to increases in permeability, a may be recognised as a proxy for porosity in the empirical equations for permeability above. Parameter a control of permeability through fracture connectivity

Fluid flow in permeable media follows Darcy's law,

v— fluid velocity in m/ s, κ = spatially variable permeability in m², μ = essentially constant fluid viscosity in Pa-s, P = pressure in Pa, and V = vector gradient operator. Combining Darcy's law with conservation of mass, dP = BV v, with B = essentially constant elastic modulus, the fluid flow time evolution is given by the advection-diffusion equation,

2

dP = Β/ ν·(κ ) = Β/μ (xV P +V¾-VP), where spatial variability in permeability κ leads to the non-vanishing gradient term Vx*VP.

The time evolving advection-diffusion equation is solved for the fluid flow field v = κ/ μ Ρ by numerical methods. Two realisations of the time-evolving advection-diffusion equation are shown in figures 4a and 4b. In figure 4a, magnitude grading of flow velocities are shown for a fluid moving from a source well to a sink well in an essentially uniformly permeable medium. In figure 4b, fluid flow velocities are shown for a non-uniform permeability medium obeying the empirical permeability relation κ,, = κ exp[u(((„— eg)] for a spatially varying porosity distribution. Figure 4b shows fluids moving along filamentary percolation channels corresponding to fracture- connectivity pathways. Figure 4a shows fluid flow velocities for a small value of parameter a, whereas figure 4b shows fluid flow velocities for a larger value of parameter a.

Control of fluid flow velocity distributions by parameter a is shown more quantitatively in figure 3. The figures show the flow velocity distribution for flow from a central pressurised well-bore to a low pressure region at the periphery of the medium. Each figure row shows (left to right) the frequency distribution of permeability in the medium, the pressure field in the medium, and the velocity field in the medium. The three rows illustrate flow distributions for successively larger values of parameter a (smallest at top, largest at bottom).

Relatively few permeability distributions observed in nature have values of parameter a as small that shown in the top row. Most permeability distributions observed in nature have values of parameter a as shown in the middle and lower rows. Flow in crustal rock thus tends to be through fracture-connectivity channels as seen in the rightmost centre and lower fluid flow velocity diagrams.

Because of the empirical definition of permeability used in constructing the above flow simulations, the distributions of permeability shown in the left-hand column are termed 'lognormal'. For low values of parameter a, lognormal distributions are substantially the same or similar to 'normal' distributions (i.e., similar to a 'bell-shaped curve'). For intermediate to large values of parameter a, lognormal distributions are increasingly skewed towards the vertical axis as many values of permeability are small, while a few values of parameter a are very large. These latter distributions reflect the increasingly heterogeneous/channelized permeability flow structure of media with high values of parameter a. Well-bore populations are usually highly skewed towards many poorly producing wells with a few abundantiy producing wells.

The above has empirically demonstrated that:

• Fracture connectivity controls flow in crustal rock,

• Parameter can be determined to analyse and/or control the degree of fracture connectivity, and

• Flow phenomena in crustal rock tend to be lognormally (intermediate to high values of a) rather than normally distributed (low values of a).

To increase flow in crustal rock volumes, one can aim to increase permeability by increasing the value of a.

In some embodiments, core samples of permeability and porosity can be taken to measure or predict alpha. The above empirical formulas may be stored in memory 120 for use by the processor 130 to determine alpha from core sample values. Information relating values of alpha with values indicative of degree of fracture connectivity within a reservoir may be alternatively or also stored in memory 120. Using well-bore fluid pressure to increase parameter a

Rock is composed of strong, tough mineral (typically silicate) grains bonded by weak cements (typically calcite and silica). Fracturing and fracture connectivity in crustal rock is mediated by irreversible strain damage induced in cement bonds during ongoing tectonic deformation. The greater the number of damage sites in a rock volume, the greater the chance that the damage centres will link up to form spatially extended percolation pathways to give the rock volume its bulk permeability (fracture connectivity). Grain-scale damage can be artificially induced in crustal rock volumes by pressurization of well- bore fluids (liquid or gas) connected to in situ fluids worldng in combination with shear stresses arising from vertical gravitational loading and horizontal tectonic forces. Large overpressures in the well-bore fluid create grain-scale damage and allow shear stresses to force rock to slip along weak internal surface structures. The overall value of the fracture-connectivity parameter, a, thus increases as a result of increased grain-scale damage induced in the rock volume by well-bore fluid pressurization.

In one aspect the invention therefore relates to a method and system for systematically controlling the increase of fracture connectivity in a crustal rock volume, by defining the fracture connectivity parameter a, and prescribing a means of measuring the increase of a during and after well-bore fluid pressurization.

Production efficiency of a well is increased b}' maximising the degree of fracture interconnectedness or connectivity throughout the rock and/ or between areas of relatively high fracture interconnectedness localised around separated defect sites in the rock, from connected breakdown of cement bonds between harder rock particles or aggregates of particles of the rock, increasing bulk permeability through the rock. In some embodiments, a model and/ or lookup table determined through experimentation prior to analysis of a particular subsurface region or reservoir may be stored in memory 120 for relating pressurisation values with values of alpha, change in alpha, rate of change of alpha or any combination thereof. For example, the table and/or model may relate any one or more of temperature, rate and/ or pressure or any other parameter associated with an injected fluid with one or more values of alpha, change in alpha, rate of change in alpha or any combination thereof. The model and/or look up table are established through injection of pressurised fluid and measurements of core sample from data sources 110 to determine the relationship between fluid injection and alpha. During injection of pressurised fluid, alpha (or a parameter associated with alpha) can be determined or predicted from the look-up table and/ or model stored in memory by relating one or more parameters of the pressurised fluid with one or more parameters of alpha. Measuring parameter a to control the increase of petmeability during well-bore fluid pressurisation

In some embodiments, alpha or change in alpha can be measured through seismic sensors 110. Grain-scale damage induced by well-bore and in situ fluid pressurization and associated shear- stress-induced slip on internal surface structures excites small seismic waves to radiate from the damage site. The radiated seismic waves can be recorded by seismic sensors 110 located in the pressurization well-bore or in associated monitoring/instrumentation well-bores 191. By recording individual damage site seismic radiation from multiple sensors 110 located in multiple locations in the observation well-bore(s) 190/191, each event can be spatially located within the pressurized rock volume.

The spatial statistics of event-by-event relative locations for a population of seismic events induced by well-bore pressurization within a crustal volume allows a measure of the fracture connectivity parameter a. As damage increases with increased well-bore pressurisation magnitude and duration, more and more induced damage sites gradually become more and more localized on fewer and fewer sub-volumes that contain more damage site rather than fewer damage sites. The most commonly used statistical measure of such localization processes is the 'two-point correlation function' (TPCF), T(t) =\f (x) fix+ή cf x where / (x) is the damage density (here nominally associated with seismic slip events and seismic wave emission) at point x in the medium, and r is an arbitrary scale distance within the volume. In many physical processes, of which damage in a rock volume is one, the behaviour of the TPCF T(r) as a function of scale distance r takes the form of a power law, T(/) ~ 1 /r^p where p is an exponent variable to be measured. Exponent p is nominally associated with a 'fractal dimension' relating numbers of events to event size or event separation; for a three-dimensional distribution of seismic events, the spatial correlation exponent p tends towards a value p ~ 3 when there is little damage in the crustal volume (the seismic damage events are not spatially well correlated), and tends towards a value p ~ 2 when there is a great deal of damage in the crustal volume (the seismic damage events are spatially correlated with a planar failure surface). The numerical simulation power-law slopes of figure 6 are spatial correlation variations on the general fractal dimension theme.

Numerical simulation data of well-pressurisation in two-dimensional media obeys the above denominated flow conditions for two different values of fracture connectivity parameter a. Figure 4 shows that the TPCF power -law exponent p varies from ~ 0.3 to ~ 0.5 for the two cases of fracture connectivity parameter a. With sufficient number of damage events and sufficient location accuracy, it is possible to securely distinguish between values of TPCF power-law exponent that differ in value by ~ 0.01. The TPCF method therefore enables monitoring and controlling of the increase of fracture connectivity parameter a as a function of damage induced by well-bore pressurization in a crustal volume. Referring to figure 2 a flow diagram of a preferred method 200 for controlling/monitoring fracture connectivity in a subsurface region as implemented by the system 100 will now be described. The method may begin with determining or predicting an initial value for alpha based on one or more physical parameters of the crustal volume (step 210). For example, rock volume porosity and rock volume permeability may be analysed to determine or predict alpha in accordance with the empirical methods and/or look up table described above. Alpha is associated with and controls reservoir fluid permeability at or near a wellbore specifically including access of reservoir fluids to and from the wellbore. This step 210 may be conducted prior to the induction of fracturing via well-bore pressuiisation. At step 220, one or more well- bores associated with the reservoir are injected with pressurised fluid from the fluid injection machine 150 for example. As described, pressurisation of the well-bore induces fracturing and increases permeability/ fracture connectivity within the reservoir 170. At step 230 the effect of pressurisation on alpha is monitored. In some embodiments, samples of permeability and porosity are taken to determine or predict alpha via the empirical formulas or look up table. Alternatively or in addition, the seismic activity due to pressurisation is monitored through seismic sensors 110 distributed within the observation well-bores 190/191. Data acquired through reservoir activity monitoring (for example, the permeability and porosity measurements and/ or the seismic sensors 110 measurements) is analysed by the processor 130 in accordance with the associated model, formula and/ or lookup table stored in memory 120, to determine the change in alpha due to pressurisation (step 240). For example, the TPCF method described above may be used to determine a value indicative of the change in alpha. The change in alpha information may be used to determine the spatial extent of pressurization activity beyond the well-bore.

In some embodiment, the processor 120 may be configured to use this information to generate pressurisation data based on, alpha, change in alpha or any other parameter or value associated with alpha (step 250). This data can then be sent to the fluid injection machine 150 (automatically or via an operator for example) to control pressurisation accordingly (step 260). For example, pressurisation may be controlled by changing the pressure, temperature, rate or any other aspect of the fluid being injected based on the pressurisation data determined at step 250. The pressurisation data may for example control termination of pressurisation when the rate of change of alpha decreases or when change in alpha or alpha reaches a threshold.

In accordance with one embodiment of the invention, the method 200 may be used to control pressurisation of a wellbore to reach a desired level of fracture connectivity or desired value of alpha or change in alpha. This desired value may be stored in memory 120 as a predetermined criteria or threshold. After determining the initial alpha at step 210, a change in alpha required to reach the desired alpha is determined at 215. After pressurisation of the well-bore, and during monitoring of the change in alpha value, a current value of alpha (or the change in alpha) is compared to the desired alpha to determine a difference (step 245). If the difference is within a predetermined threshold stored in memory then the processor may output pressurisation data indicative of termination of pressurisation. At step 270, fluid injection is terminated when the alpha value is at the desired level. It will be appreciated that other predetermined criteria related to alpha and fracture connectivity may be stored in memory 130 for the system 100 to utilise during fracture connectivity monitoring/ control.

The system 100 thus provides a platform for monitoring and controlling fracture connectivity in the crustal rock volume by providing a means to quantify fracture connectivity or a change in fracture connectivity through pressurisation. The system 100 may further comprise drilling equipment for drilling one or more well-bores before or after increasing the fracture connectivity. The system 100 may also further comprise extraction equipment for extracting natural resources such as oil, gas, hot water, or minerals through well-bores formed in a reservoir that has been subjected to pressurisation and monitored to increase fracture connectivity in accordance with the method or methods described above.

Embodiments may be implemented by hardware, software, firmware, middleware, microcode, or any combination thereof. The methods or algorithms described in connection with the examples disclosed herein may be embodied directly in hardware, in a software module executable by a processor, or in a combination of both, in the form of processing unit, programming instructions, or other directions, and may be contained in a single device or distributed across multiple devices. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD- ROM, or any other form of storage medium known in the art. A storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. In the foregoing, a storage medium may represent one or more devices for storing data, including read-only memory (ROM), random access memory (RAM), magnetic disk storage mediums, optical storage mediums, flash memory devices and/ or other machine readable mediums for storing information. The terms "machine readable medium" and "computer readable medium" include, but are not limited to portable or fixed storage devices, optical storage devices, and/or various other mediums capable of storing, containing or carrying instruction(s) and/ or data.

The various illustrative logical blocks, modules, circuits, elements, and/ or components described in connection with the examples disclosed herein may be implemented or performed with any combination of one or more of the following implementation mediums: general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic component, discrete gate or transistor logic, discrete hardware components, designed to perform the one or more functions described herein. To perform the various functions and transfer information between the blocks, modules, circuits, elements and/ or components described, the implementation mediums may be communicatively coupled either directly or via any suitable communications network as is well known in the arts of electrical and software engineering. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, circuit, and/ or state machine. A processor may also be implemented as a combination of computing components, e.g., a combination of a DSP and a microprocessor, a number of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

One or more of the components and functions illustrated the figures may be rearranged and/ or combined into a single component or embodied in several components without departing from the invention. Additional elements or components may also be added without departing from the invention.

In its various aspects, the invention can be embodied in a compute -implemented process, a machine (such as an electronic device, or a general purpose computer or other device that provides a platform on which computer programs can be executed), processes performed by these machines, or an article of manufacture. Such articles can include a computer program product or digital information product in which a computer readable storage medium containing computer program instructions or computer readable data stored thereon, and processes and machines that create and use these articles of manufacture. The foregoing describes the invention including preferred forms thereof and alterations and modifications as will be obvious to one skilled in the art are intended to be incorporated in the scope thereof as defined in the accompanying claims.

Claims

CLAIMS:

1. A method for monitoring fracture connectivity in a geo thermal or hydrocarbon reservoir comprising the steps of:

2. A method according to claim 1 wherein the step of determining or predicting alpha comprises or the step of determining a change in alpha or both comprises determining or predicting alpha empirically from rock volume porosity and rock volume permeability.

3. A method according to either one of claim 1 or claim 2 wherein assessing one or more physical parameters of rock volume comprises assessing one to N samples (where N is equal to or greater than 1) of well-core permeability values, κ„, and well-core porosity values, φ„.

4. A method according to any one of claims 1 to 3 wherein determining or predicting alpha comprises determining from the measured parameters the ratio of a standard deviation of the logarithm of the well-core permeability values, /¾κ„, and a standard deviation of well-core porosity values, φ,

a≡ %,/ σ_φ.

5. A method according to any one of the preceding claims further comprising after determining or predicting alpha pressurising a fluid through a well-bore associated with the geothermal or hydrocarbon reservoir, and the step of determining a change in alpha over time comprises determining a change in alpha over time to monitor changes in fracture connectivity within the reservoir surrounding the well-bore due to the induction of pressurised fluid.

6. A method according to claim 5 wherein determining the change in alpha comprises measuring and/or monitoring seismic events induced by the step of pressurising the fluid through the well-bore.

7. A method according to claim 6 wherein determining the change in alpha further comprises determining spatial statistics of relative locations for a population of seismic events induced by well-bore pressurization.

8. A method according to any claim 7 wherein the spatial statistics are determined using a 'two-point correlation function' (TPCF), T(t) =J (x) (x+r) (fx where/ (x) is a damage density at point x in the medium, and ris an arbitrary scale distance.

9. A method according to claim 8 wherein determining the change in alpha further comprises determining an exponent variable, p, from the following equation:

T(r) ~ l/r^p.

10. A method for controlling fracture connectivity in a crustal rock volume of a geothermal or hydrocarbon reservoir comprising the steps of:

determining a change in a parameter indicative of fracture connectivity (hereinafter: alpha) in response to wellbore fluid pressurisation to monitor, validate or measure change in fracture connectivity due to wellbore fluid pressurisation.

11. A method according to claim 10 wherein determining the change in alpha is performed during or after the step of pressurising the reservoir fluid through the well-bore.

12. A method according to either claim 10 or claim 11 wherein determining the change in alpha comprises measuring and/ or monitoring seismic events induced by the step of pressurising the reservoir fluid through the well-bore.

13. A method according to claim 12 wherein determining the change in alpha further comprises determining spatial statistics of relative locations for a population of seismic events induced by well-bore fluid pressurization.

14. A method according to any claim 13 wherein the spatial statistics are determined using a 'two-point correlation function' (TPCF), T(i)—1/(χ) χ+ή ( x where f (x) is a damage density at point x in the medium, and r is an arbitrary scale distance within the volume.

15. A method according to claim 14 wherein determining the change in alpha further comprises determining an exponent variable,^, from the following equation:

T{r) ~ l/r^p.

16. A method according to any one of claim 10 to claim 15 further comprising prior to pressurising the fluid through the well-bore, assessing one or more physical parameters of the crustal rock volume in situ to determine or predict an initial value of alpha.

17. A method according to claim 16 wherein the step of determining or predicting alpha comprises determining or predicting alpha empirically from rock volume porosity and rock volume permeability.

18. A method according to either one of claim 16 or claim 17 wherein assessing one or more physical parameters of rock volume comprises assessing one to N samples (where N is equal to or greater than 1) of well-core permeability values, κ„, and well-core porosity values, φ„.

19. A method according to any one of claims 16 to 18 wherein determining or predicting alpha comprises determining from the measured parameters the ratio of a standard deviation of the logarithm of the well-core permeability values, /<¾κ„, and a standard deviation of well-core porosity values, φ„:

«≡ %/ σ_φ.

20. A method according to any one of claims 10 to 19 further comprising the step of determining pressurisation data based on the change in alpha for controlling pressurisation of a fluid through a wellbore associated with the reservoir.

21. A method for determining pressurization of a well-bore in a geothermal or hydrocarbon reservoir comprising the steps of:

determining a change in the parameter indicative of fracture connectivity (hereinafter: alpha), and

22. A method according to claim 21 further comprising during or after or both during and after determining the change in alpha, pressurising a fluid through a well-bore associated with the geothermal or hydrocarbon reservoir in accordance with the pressurisation data.

23. A method according to either one of claim 21 to claim 22 wherein the step of generating reservoir pressurisation data comprises comparing the determined change in alpha with a desired value of alpha or a desired value of change in alpha, and generating reservoir pressurisation data based on the comparison to achieve the desired alpha or the desired change in alpha.

24. A method according to any one of claim 21 to claim 23 further comprising before determining the change in alpha, pressurising a fluid through a well-bore associated with the geothermal or hydrocarbon reservoir.

25. A method as claimed in any one of claim 21 to claim 23 further comprising prior to determining the change in alpha, assessing one or more physical parameters of the crustal rock volume in situ to determine or predict alpha.

26. A method according to claim 25 wherein the step of determining or predicting alpha comprises determining or predicting alpha empirically from rock volume porosity and rock volume permeability.

27. A method according to either one of claim 25 or claim 26 wherein assessing one or more physical parameters of rock volume comprises assessing one to N samples (where N is equal to or greater than 1) of well-core permeability values, κ„, and well-core porosity values, φ„.

28. A method according to any one of claim 25 to claim 27 wherein determining or predicting alpha comprises deterrnining from the measured parameters the ratio of a standard deviation of the logarithm of the well-core permeability values, /¾κ„, and a standard deviation of well-core porosity values, φ„:

α≡ %Λ_φ·

29. A method according to any one of claim 21 to claim 28 wherein determining the change in alpha comprises measuring and/ or monitoring seismic events induced by the step of pressurising the fluid through the well-bore.

30. A method according to claim 29 wherein determining the change in alpha further comprises determining spatial statistics of relative locations for a population of seismic events induced by well-bore pressurization.

31. A method according to claim 30 wherein the spatial statistics are determined using a 'two-point correlation function' (TPCF), T(t ⁼J (·*) ./(· '+'") c?x where f (x) is a damage density at point x in the medium, and ris an arbitrary scale distance.

32. A method according to claim 31 wherein determining the change in alpha further comprises determining an exponent variable,^), from the following equation:

T(r) ~ l/r^p.

33. A method for monitoring permeability in a geothermal or hydrocarbon reservoir comprising the steps of:

34. A method for controlling permeability in a crustai rock volume of a geothermal or hydrocarbon reservoir comprising the steps of:

determining a change in a parameter indicative of fracture connectivity (hereinafter: alpha) in response to pressurisation to validate change in fracture connectivity due to pressurisation.

35. A method for determining pressurization of a well-bore in a geothermal or hydrocarbon reservoir comprising the steps of:

determining a change in a parameter indicative of fracture connectivity (hereinafter: alpha), and

36. A system for monitoring or controlling fracture connectivity in a geothermal or hydrocarbon reservoir, the system comprising:

a processing component configured to:

37. A system according to claim 36 wherein the processor is further configured to generate pressurisation data according to the change in alpha for pressurisation of the well-bore.

38. A system according to either claim 36 or claim 37 further comprising a fluid injection machine configured to pressurise a wellbore associated with the reservoir to induce fracturing.

39. A system according to claim 38 wherein the processor is configured to generate pressurisation data according to the change in alpha and the fluid injection machine is configured to pressurise the wellbore in accordance with the pressurisation data.

40. A system according to any claim 36 or claim 39 wherein the processor is configured to receive data indicative of seismic events induced by pressurising of fluid through a well-bore associated with the reservoir and determine the change in alpha using the received seismic event data.

41. A system according to claim 40 wherein the processor is configured to determine the change in alpha bj determining spatial statistics of relative locations for a population of seismic events induced by well-bore pressurization.

42. A system according to claim 41 wherein the processor is configured to determine spatial statistics using a 'two-point correlation function' (TPCF), T{f)—ί/(χ) βχ+ή c?x where / (x is a damage density at point x in the medium, and r is an arbitraiy scale distance within the volume.

43. A system according to claim 42 wherein the processor is configured to determine the change in alpha by determining an exponent variable, /¾ according to the following equation:

T(r) ~ l/r^p.

44. A system according to any one of claim 40 to claim 43 further comprising a plurality of seismic sensors configured to obtain data indicative of seismic events induced by pressurisation.

45. A system according to any one of claim 36 to claim 44 wherein the processor is further configured to assess one or more physical parameters of the crustal rock volume in situ to determine or predict an initial value of alpha and store the initial value of alpha in the memory component.

46. A system according to claim 45 wherein the processor is configured to receive data indicative of rock volume porosity and data indicative of rock volume permeability and determine or predict alpha empirically from the rock volume porosity data and the rock volume permeability data.

47. A s}rstem according to either one of claim 45 or claim 46 wherein the processor is configured to assess one or more physical parameters of rock volume by assessing one to N samples (where N is equal to or greater than 1) of well-core permeability values, κ„, and well-core porosity values, φ„.

48. A system according to any one of claims 45 to 47 wherein the processor is configured to determine or predict alpha by determining from the physical parameters the ratio of a standard deviation of the logarithm of the well-core permeability values, /¾κ„, and a standard deviation of well-core porosity values, φ„:

a = %</ < 49. A method for determining pressurization of a well-bore in a geothermal or hydrocarbon reservoir comprising the steps of:

assessing one or more physical parameters of the crustal rock volume in situ to determine or predict a parameter indicative of fracture connectivity in the rock medium surrounding the wellbore,

determining a change in the parameter indicative of fracture connectivity, and utilising the change in the parameter to determine the spatial extent of pressurization activity beyond the well- bore.