BACKGROUND

Horizontal drilling and hydraulic fracturing operation are widely used to develop low-permeability unconventional plays. Horizontal drilling is a technology that drills a well at a certain depth horizontally. The well path usually follows the formation of interest to increase contact with the reservoir rocks. Hydraulic fracturing operation includes injecting a large volume of water and proppant mixture (slurry) into the horizontal wells. The slurry enters the reservoir through the designed perforations and creates fractures hydraulically inside the reservoir. After the injection stops, as the injected water leaks off through the fracture into the reservoir matrix, the proppant remains in the fractures to keep them open. The hydrocarbon resources within the reservoir rock matrix slowly flow through the propped fractures into the well during the production stage.

The most important design decisions for unconventional reservoir development are well spacing and fracturing parameters. These designs significantly, if not deterministically, affect the cost of hydrocarbon production. As a result, they need to be optimized to achieve better economic results. Well spacing refers to the vertical or horizontal distances between the horizontal section of adjacent wells. Large well spacing may risk leaving resources behind, which increases average land leasing cost; while small well spacing may lead to underperformance due to production interference between the wells, and increases the drilling and completion cost of the field. Fracturing parameters include perforation cluster spacing, number of clusters per stage, injection volume, proppant concentration, proppant size, etc. More intensive fracturing designs (e.g. higher injection volume, shorter cluster spacing) may generate denser and longer fracture networks, at the expense of increased completion cost. On the other hand, less intensive fracturing designs may cause poor production performance and reduced recovery rate. Optimizing these parameters is the key to the success of unconventional reservoir development.

The geometry of Drainage Reservoir Volume (DRV) is one of the most important factors to consider when determining well spacing and fracturing parameters. DRV is defined as the rock volume within which the well drains the hydrocarbon during its lifespan. For unconventional reservoirs, DRV highly correlates with the geometry of propped hydraulic fractures, which are the fractures with proppant inside and remaining conductive during the production stage. The geometry of DRV is determined by hydraulic fracture geometry and proppant transportation within the fractures (Raterman et al. 2019). Hydraulic fracture geometry is controlled by factors including local stress anisotropy, rock geomechanical properties, reservoir heterogeneities, pre-existing natural fractures, injection fluid viscosity, etc. Proppant transportation within the fractures can be affected by fracture surface roughness, natural fracture interference, fracture fluid leak-off rate, proppant size, and other factors. It is very difficult, even impossible in most cases, to accurately predict or model the DRV geometry using numerical simulation.

Currently, there are very few methods that measure the DRV directly. Radioactive tracers can be added to the proppant for later detection after the injection using a downhole tool (e.g. Stromswold 1990). This method can measure the proppant distribution around the injection well, but the detection radius is very small (less than a foot) and cannot provide DRV information at far-field. Palisch et al. (2016) proposed using electromagnetic methods to detect proppant mixed with metal particles in the formation. This method can provide far-field proppant distribution but is subject to low spatial resolution and has not been commercialized. Geochemistry analysis of the produced oil can reveal the geometry of vertical drainage (e.g. Liu et al. 2017), however it does not put constraints on horizontal well spacing.

Fiber-Optic Sensing (FOS) technology has become popular in the oil industry in recent years. The latest development has enabled several FOS applications for hydraulic fracturing monitoring, including injection allocation (e.g. Boone et al. 2015), hydraulic-fracture geometry constraint (Jin & Roy 2017), microseismic monitoring (e.g. Webster et al. 2013), and others. Among the various service providers, Neubrex Co., Ltd. developed a FOS solution that is unique in the industry (e.g. Kishida et al. 2014). By deploying a single cable (FIG. 9), the system measures distributed temperature, strain, and pressure variations along the fiber with high spatial and temporal resolution. The frequency shifts are known to be expressed as:
ΔvB=C11Δε+C12ΔT+C13ΔP(1)
ΔvR=C21Δε+C22ΔT+C23ΔP(2)
where ΔvBand ΔvRare the frequency shift of Brillouin and Rayleigh backscattering light at the specific location.

The FOS system developed by Neubrex is known as a distributed optical fiber measurement system (hereinafter, abbreviated as “measurement system”) which measures the pressure, temperature, and strain of a measurement object all at once by using frequency information about Rayleigh scattering and Brillouin scattering of an optical fiber (for example, International Publication No. 2014-181617).

Here, Rayleigh scattering light has characteristics that, when the scattering light obtained by light entering an optical fiber is subjected to frequency analysis, the scattering light has almost the same frequency as the entering light, and meanwhile, Brillouin scattering light has characteristics that the frequency thereof is different from that of the entering light by about several to several ten GHz.

Rayleigh scattering is a scattering phenomenon caused by light scattering due to fluctuation of the refractive index in an optical fiber, and the frequency difference between entering light and Rayleigh scattering light is Rayleigh frequency. The Rayleigh frequency changes due to strain, temperature, or pressure applied to the optical fiber, and hereafter, this change is referred to as Rayleigh frequency shift ΔvR.

On the other hand, Brillouin scattering is a phenomenon in which, when light enters an optical fiber, power transfers via an acoustic phonon of the optical fiber, and the frequency difference between the entering light and Brillouin scattering light is Brillouin frequency. The Brillouin frequency is proportional to the speed of sound in the optical fiber, and the speed of sound depends on the strain and temperature of the optical fiber. Therefore, it is possible to measure the strain, temperature, or pressure applied to the optical fiber by measuring change in the Brillouin frequency. Hereafter, this change is referred to as Brillouin frequency shift ΔvB.

A typical example of the above measurement system is an optical fiber cable system having an armored cable. An optical fiber cable used in this system is provided with multilayer armored wires, and made up of a fiber in metal tube (FIMT) which is an optical fiber having a sensor function such as a temperature sensor, an optical waveguide which is a sensor function part of an optical fiber core, and others. This cable is fixed to a stratum by cementing or the like.

The above measurement system includes a hybrid-type backscattered light measuring device configured to cause light to enter the above two kinds of optical fibers and then measure and analyze a Rayleigh frequency shift ΔvRand a Brillouin frequency shift ΔvBwhich are frequency shifts between the entering light and the scattering light in the two kinds of optical fibers and which are frequency shifts having properties different from each other.

The measurement system configured as described above can accurately measure distributions of pressure P, temperature T, and strain c of a borehole which is a measurement target, all at once.

In this case, the Brillouin frequency shift ΔvBand the Rayleigh frequency shift ΔvRcan be respectively represented as shown by the above Eqs. (1) and (2) using a pressure change amount ΔP, a temperature change amount ΔT, and a strain change amount Δε.

Here, in Eqs. (1) and (2), Cijis a coefficient specific to each optical fiber. If these coefficients are calculated in advance for the optical fibers to be used, it is possible to calculate distributions of the pressure change amount ΔP, the temperature change amount ΔT, and the strain change amount Δε as described below.

Here, it is assumed that ΔvBand ΔvRhave been measured. With these measured values, in order to calculate each of the pressure P, the temperature T, and the strain c separately from each other without each other's influence, at least three or more independent measurement quantities are needed. Only two independent measurement values ΔvBand ΔvRare obtained with one optical fiber. Therefore, in order to obtain three or more independent measurement quantities, here, two kinds of optical fibers having different sensitivities with respect to the pressure change amount ΔP, the temperature change amount ΔT, and the strain change amount ΔE are used, thereby obtaining four independent measurement values (see the following Eq. (3)).

Δ⁢⁢vB1=C111⁢Δ⁢⁢ɛ1+C121⁢Δ⁢⁢T+C131⁢Δ⁢⁢PΔ⁢⁢vR1=C211⁢Δ⁢⁢ɛ1+C221⁢Δ⁢⁢T+C231⁢Δ⁢⁢PΔ⁢⁢vB2=C112⁢Δ⁢⁢ɛ2+C122⁢Δ⁢⁢T+C132⁢Δ⁢⁢PΔ⁢⁢vR2=C212⁢Δ⁢⁢ɛ2+C222⁢Δ⁢⁢T+C232⁢Δ⁢⁢P}(3)

Here, the superscript numerals denote the kinds of the optical fibers. The pressure and the temperature are those at the field where the optical fibers exist, and therefore have the same values between the two kinds of fibers. On the other hand, the value of strain depends on whether or not the optical fiber is fixed to the surrounding object. In a distributed pressure, temperature and strain system (DPTSS), it is necessary to measure strain of the surrounding object around the fiber, and therefore at least one optical fiber needs to be fixed to the surrounding object.

Accordingly, by solving simultaneous equations in the above Eq. (3), it is possible to separate the influences of the pressure P, the temperature T, and the strain c from each other. Therefore, by performing hybrid measurement including Brillouin frequency shift measurement (hereafter, may be referred to as Brillouin measurement) and Rayleigh frequency shift measurement (hereafter, may be referred to as Rayleigh measurement) using the above measurement system, and then solving the simultaneous equations in Eq. (3), it is possible to calculate distributions of the pressure change amount ΔP, the temperature change amount ΔT, and the strain change amount ΔE along the optical fiber.

Next, the measurement procedure in the above measurement system will be described. First, regarding Brillouin scattering, the Brillouin frequency shift ΔvBbetween entering light and scattering light is represented by Eq. (4).

Δ⁢⁢vB1=C111⁢Δ⁢⁢ɛ1+C121⁢Δ⁢⁢T+C131⁢Δ⁢⁢PΔ⁢⁢vB2=C112⁢Δ⁢⁢ɛ2+C122⁢Δ⁢⁢T}(4)

Here, the superscript numerals of ΔvBdenote the kinds of optical fibers: “1” refers to the optical waveguide and “2” refers to the FIMT. The coefficients Cijare sensitivity coefficients specific to the optical fibers, and the superscript numerals refer to the respective kinds of optical fibers as with the above. The superscript numerals of c also refer to the respective kinds of optical fibers as with the above. In addition, that no term relating to ΔP appears in the expression at the lower stage in Eq. (4) is due to the fact that the FIMT is isolated from influence of pressure.

Next, the Rayleigh frequency shift ΔvRis represented by the following Eq. (5).

Δ⁢⁢vR1=C211⁢Δ⁢⁢ɛ1+C221⁢Δ⁢⁢T+C231⁢Δ⁢⁢PΔ⁢⁢vR2=C212⁢Δ⁢⁢ɛ2+C222⁢Δ⁢⁢T}(5)

Here, the superscript numerals of ΔvRdenote the kinds of optical fibers: “1” refers to the optical waveguide and “2” refers to the FIMT. In addition, that no term relating to ΔP appears in the expression at the lower stage in Eq. (5) is due to the fact that the FIMT is isolated from influence of pressure. The definitions of the other symbols are the same as those with ΔvB; hence, they are omitted here.

From these Eqs. (4) and (5), using characteristic coefficients Dij(which are characteristic coefficients based on frequency shifts and determined as the inverse matrix of Cij) determined from the sensitivity coefficients Cij, a relationship expressed by the following Eq. (6) holds true between: the pressure change amount ΔP, the temperature change amount ΔT, and the strain change amount Δε; and ΔvBand ΔvR.

(Δ⁢⁢PΔ⁢⁢TΔɛ1Δɛ2)=(Dij)⁢(Δ⁢⁢vB1Δ⁢⁢vR1Δ⁢⁢vB2Δ⁢⁢vR2)(6)

Thus, the pressure change amount ΔP, the temperature change amount ΔT, and the strain change amount Δε of a measurement object can be calculated from the measurement values of the frequency shifts, using Eq. (6).

In addition, from Eqs. (4) to (6), the temperature T, the strain c, and the pressure P can be specifically calculated using the following Eqs. (7) to (9), respectively. Here, the superscript “FIMT” in Eq. (7) and the superscript “strain” in Eq. (8) correspond to “2” in the left-hand side of the expression at the lower stage in Eq. (5).

For the example inFIG. 9, it is possible to get strain and pressure by only utilize the Rayleigh DTSS which has a higher precision than Brillouin. It was discovered as follows:
T=T0+ΔT=T0+ΔvRFIMT/C22(7)
ε=ε0+Δε=ε0+(ΔvRstrain−ΔTC22)/C21(8)
P=P0+ΔP=P0+(ΔvRP−ΔTC22−ΔεC21)/C23(9)

There are other possibilities of proper deployments, this technology can provide critical information to constrain DRV geometry and to optimize well spacing as well as fracturing parameters.

