U.S. patent application number 17/066519 was filed with the patent office on 2021-12-16 for methods of determining borehole characteristics.
This patent application is currently assigned to Neubrex Co., Ltd.. The applicant listed for this patent is Neubrex Co., Ltd.. Invention is credited to Ge Jin, Kinzo Kishida.
Application Number | 20210388718 17/066519 |
Document ID | / |
Family ID | 1000005161129 |
Filed Date | 2021-12-16 |
United States Patent
Application |
20210388718 |
Kind Code |
A1 |
Jin; Ge ; et al. |
December 16, 2021 |
METHODS OF DETERMINING BOREHOLE CHARACTERISTICS
Abstract
A method of determining borehole characteristics comprises
arranging at least one sensing fiber along a borehole, causing
pressure changes in the borehole, and measuring strain along the
sensing fiber to obtain strain data. The strain data obtained
thereby can be interpreted, for example, to determine borehole
fracture geometry and to determine borehole perforation cluster
efficiency. These results can be used to improve well completion
and stimulation designs, increase field production, and/or decrease
costs.
Inventors: |
Jin; Ge; (Houston, TX)
; Kishida; Kinzo; (Kobe-shi, JP) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Neubrex Co., Ltd. |
Kobe-shi |
|
JP |
|
|
Assignee: |
Neubrex Co., Ltd.
Kobe-shi
JP
|
Family ID: |
1000005161129 |
Appl. No.: |
17/066519 |
Filed: |
October 9, 2020 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
62705078 |
Jun 10, 2020 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
E21B 47/007 20200501;
E21B 49/008 20130101; E21B 47/06 20130101; E21B 47/114
20200501 |
International
Class: |
E21B 49/00 20060101
E21B049/00; E21B 47/007 20060101 E21B047/007; E21B 47/06 20060101
E21B047/06 |
Claims
1. A method of determining borehole characteristics comprising:
arranging at least one sensing fiber along a borehole; causing
pressure changes in the borehole; and measuring strain along the at
least one sensing fiber to obtain strain data.
2. The method of claim 1, wherein the borehole along which the at
least one sensing fiber is arranged has been fractured.
3. The method of claim 2, further comprising: determining borehole
fracture geometry based on the strain data.
4. The method of claim 2, wherein the borehole along which the at
least one sensing fiber is arranged has been hydraulically
fractured.
5. The method of claim 2, wherein the borehole along which the at
least one sensing fiber is arranged has been naturally
fractured.
6. The method of claim 1, wherein the borehole along which the at
least one sensing fiber is arranged is a borehole of a vertical
producer well or of a vertical injector well.
7. The method of claim 1, wherein the borehole along which the at
least one sensing fiber is arranged is a borehole of a conventional
well.
8. The method of claim 1, further comprising: determining borehole
perforation cluster efficiency based on the strain data.
9. The method of claim 1, wherein the at least one sensing fiber
includes at least one optic fiber.
10. The method of claim 1, wherein the causing of the pressure
changes in the borehole includes at least one selected from the
group consisting of: shutting-in the borehole, changing a choke
size of the borehole, or performing an injection in the
borehole.
11. The method of claim 1, wherein the measuring of strain along
the at least one sensing fiber is performed before the pressure
changes to obtain a baseline strain reading, during pressure
changes to obtain time-dependent strain variation data, and after
the pressure changes to obtain strain recovery data, wherein the
strain data includes the baseline strain reading, the
time-dependent strain variation data, and the strain recovery
data.
12. The method of claim 1, wherein the measuring of strain along
the at least one sensing fiber includes performing distributed
strain sensing.
13. The method of claim 1, further comprising: measuring
temperature along the at least one sensing fiber to obtain
temperature data.
14. The method of claim 1, further comprising: obtaining pressure
data from the borehole; and comparing the pressure data to the
strain data to obtain cluster performance data.
15. The method of claim 1, wherein the borehole is a borehole of a
well undergoing production, and the method further comprises:
ceasing production from the well prior to the causing of the
pressure changes in the borehole; and resuming production from the
well after the causing of the pressure changes in the borehole.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application claims the benefit of Provisional U.S.
Patent Application Ser. No. 62/705,078 filed on Jun. 10, 2020, the
contents of which are incorporated herein by reference in their
entireties for all purposes.
TECHNICAL FIELD
[0002] The present disclosure relates to a method of determining
borehole characteristics, and more particularly, for example, for
near-wellbore hydraulic fracture and perforation efficiency
diagnosis using distributed sensing measurements.
BACKGROUND INFORMATION
[0003] Productions from unconventional reservoirs (e.g., shale,
tight sandstone) play an important role in the energy market. The
development of unconventional reservoirs was enabled by two key
technologies: horizontal drilling and hydraulic fracturing.
Horizontal drilling technology can horizontally deploy a borehole
for tracking the targeted formation in the deep subsurface to
increase the contact length to the reservoir. Hydraulic fracturing
can generate hydraulic fractures in the target reservoir by
injecting mixtures of water, chemicals, and proppant (fine-grain
sand, ceramic, or other materials) into the reservoir with
extremely high pressure. The generated hydraulic fractures can
increase the effective permeability of the original tight
(low-permeability) reservoir rocks, and can enhance the migration
of hydrocarbons (oil and gas) within the reservoir. The hydraulic
fracturing operation is usually referred to as reservoir
stimulation, which is part of well completion procedures.
[0004] In order to improve production performance, the hydraulic
fractures should be generated as evenly as possible in the
reservoir. The wellbore portion within the reservoir is usually
divided into small sections which are stimulated individually. Each
section is referred to as a stage. Within a stage, several entry
points to the reservoir are created in the wellbore, allowing the
injected fluid to enter the reservoir and generate hydraulic
fractures. The entry points are usually referred to as perforations
or perforation clusters. That is, a perforation is the channel
through which the pressure communicates between the near-wellbore
hydraulic fracture system and the borehole. Hydraulic fractures
will typically be initiated at the entry points and grow into the
reservoir with complex geometry (see, e.g., Raterman et al. 2018),
which is controlled by the reservoir rock property, reservoir
stress condition, pre-existing geological structures, and hydraulic
fracturing designs. Hydraulic fracturing designs can include, but
are not limited to, variations in perforation cluster spacing,
number of perforation cluster per stage, injection volume,
injection rate, proppant concentration, injection fluid viscosity,
injection chemical combination, etc.
[0005] During the production stage, hydrocarbons migrate from the
rock matrix to the well through the created hydraulic fractures
network, driven by the pressure gradient, with the borehole having
the lowest pressure. As the pressure depletes due to production,
the aperture (width) of hydraulic fractures decreases due to the
pressure difference between the rock matrix and fluid within the
fractures. The proppant injected during the pumping stage is
designed to support the fracture aperture with its mechanical
strength (see, e.g., Kurz et al. 2013) after the fracture aperture
is reduced to a certain level. After this point, the fracture
aperture still decreases with pressure due to the elastic
deformation of proppant grains, but at a different rate compared to
the fractures that are not supported by proppant.
[0006] Existing methods of field observations that can be used to
constrain near-wellbore (i.e., <30 m from the well opening)
fracture properties are quite limited. Many techniques have been
developed to evaluate hydraulic fractures in the far field (>10
m away from the well), including microseismic monitoring (see
Calvez et al. 2007; Baan et al. 2013; Maxwell et al. 2010),
low-frequency strain monitoring (see, e.g., Jin and Roy 2017), core
analysis (see Raterman et al. 2018), pressure analysis (see Seth et
al. 2019), etc. More recently, special attention has been made to
the near-field (near-wellbore) hydraulic fracture properties.
Near-wellbore fracture properties heavily influence the well's
production performance because all the produced hydrocarbons pass
through this fracture network before entering the borehole through
perforations. Laboratory and numerical modeling work has been done
to understand the near-wellbore fracture properties (see
Fallahzadeh et al. 2017; Dong and Tang 2019). However, very limited
field observations can help to constrain the actual near-field
fracture geometry. Raterman et al. (2018) used core extraction to
analyze near-wellbore hydraulic fractures. However, this method
requires drilling a horizontal monitor wellbore close and parallel
to the stimulated well, which is extremely expensive, and exposed
the risk of damaging existing wellbore. Ugueto et al. (2019)
discusses using temperature warmback signal to constrain
near-wellbore fracture geometry. However, temperature measurements
can be affected by many factors, including cross-flow between
perforations, far-field production fluid warming, near-field
thermal diffusion, etc. Moreover, the borehole temperature
signature diminishes after a certain period of production due to
thermal conduction between wellbore fluid and reservoir rocks. As a
result, this method cannot provide long-term, high-quality
monitoring of near-wellbore fracture geometry and properties.
[0007] Moreover, current methods cannot efficiently evaluate
perforation cluster efficiency for modern unconventional wells.
Perforation efficiency is defined as the percentage of production
contribution of the perforation or perforation cluster to the total
production of the well. To actually evaluate perforation
efficiency, a production logging operation (see Daniel Hill 1990)
is typically needed. However, traditional production logging
operation through well intervention in horizontal unconventional
wells is quite challenging and expensive (see, e.g. Heddleston
2009; Miklashevskiy et al. 2017). Some recent developments have
been made to explore non-intrusive production logging methods (see
Ovchinnikov et al. 2017; Jin et al. 2019), but these methods suffer
high-uncertainty and non-unique results. Moreover, all
aforementioned production logging methods cannot provide results
with a spatial resolution comparable to modern perforation cluster
spacings (5-100 ft). Near-wellbore fracture properties are highly
correlated with perforation efficiency. With a proper estimation of
near-wellbore fracture properties, perforation cluster efficiency
can be evaluated. More importantly, the relation between
perforation cluster efficiency and hydraulic fracturing designs can
be established in the same stimulation well to accelerate hydraulic
fracturing design optimization in the reservoir development.
[0008] Distributed strain measurements have not been effectively
taken in a producing well. There is a growing trend in the oil
industry that utilizes Distributed Fiber-Optic Sensing (DFOS)
technology to monitor and evaluate hydraulic fracturing operations
and later production performance of unconventional wells. Current
applications include perforation injection allocation (see, e.g.
Boone et al. 2015), microseismic monitoring (see, e.g. Webster et
al. 2013), and production logging (see, Jin et al. 2019). More
recently, it has become popular to use Distributed Strain Sensing
(DSS) to monitor mechanical strain variations for hydraulic
fracturing monitoring (see Jin and Roy 2017). Typical DSS
applications however focus on measurements from an offset monitor
well (cross-well monitoring), instead of the actual producing well
(in-well monitoring). As such, little near-wellbore fracture
information can be obtained.
[0009] Furthermore, multiple physical effects cannot be separated
in the measured DFOS data. When a DFOS method is used for
near-wellbore deformation measurements, the fiber optic will
subjected not only to strain, but also subjected to temperature,
pressure and other physics variables. Due to the injection and
production activities, the thermal strain induced by borehole
temperature variations are usually larger or comparable to the
interested mechanical strain signals, which is one of the main
challenges to use DSS for in-well measurements.
[0010] The sensitivity and resolution of current DSS measurements
are also limited. The mechanical strain variation during production
period in the producing well is usually small and localized around
the perforation locations. The sensitivity and spatial resolution
of previous Brillouin-based (see, e.g., Hong et al. 2017) or
low-frequency Distributed Acoustic Sensing (DAS) based (see, e.g.,
Jin and Roy 2017) DSS measurements are typically insufficient to
capture the desired signal.
SUMMARY
[0011] A method of determining borehole characteristics is
disclosed and comprises arranging at least one sensing fiber along
a borehole which has been hydraulically fractured, causing pressure
changes in the borehole, and measuring strain along the sensing
fiber to obtain strain data.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] Other features and advantages disclosed herein will become
more apparent from the following detailed description of
illustrative embodiments when read in conjunction with the attached
drawings.
[0013] FIG. 1 is a schematic representation of an illustrative
method of determining borehole characteristics.
[0014] FIG. 2 is a schematic representation of an illustrative well
operation and data acquisition sequence to diagnose near-wellbore
fracture and perforation efficiency.
[0015] FIG. 3 is a schematic representation of an illustrative
process of using distributed strain sensing to measure
near-wellbore fracture geometry and property.
[0016] FIG. 4 is a schematic representation of illustrative strain
data obtained from distributed strain sensing measurement of strain
variation due to a shut-in operation on an unconventional oil
producer, where black triangles depict perforation cluster
locations, while a dashed horizontal line separates extension and
compression zones.
[0017] FIG. 5 is a schematic representation of an illustrative
comparison of strain variation at perforation clusters of two
different hydraulic fracturing designs in the same unconventional
well, where black dot and error bars show the mean and standard
deviation of the strain variation of a given design.
DETAILED DESCRIPTION
[0018] Due to the complexity of fracture propagation processes and
uncertainty of local rock properties and geological condition, the
actual hydraulic fracture geometry and property can be quite
difficult to predict by analytical or numerical models (see
Raterman et al. 2018). Moreover, understanding the geometry and
property of hydraulic fractures can also be quite helpful for
optimizing the development of unconventional reservoirs. Different
designs of fracturing operations could lead to various hydraulic
fracturing and proppant transportation results (see Zeng and Guo
2016; Curnow and Tutuncu 2016), which can significantly affect the
production performance during the later production period.
[0019] The present disclosure describes illustrative methods
utilizing Distributed Temperature and Strain Sensing (DTSS)
technology to evaluate near-wellbore fracture properties and
perforation cluster efficiency, by measuring the in-well mechanical
strain variations induced by borehole pressure changes.
[0020] Borehole pressure, which is defined as the fluid pressure
inside the wellbore, can change dramatically due to such well
operations as injection, production, and shut-in. During injection,
borehole pressure is artificially increased by the pumping activity
from the surface. During production, because hydrocarbon and water
are extracted from the reservoir to the surface, either by the
reservoir pressure or by artificial lift equipment, the borehole
pressure slowly decreases overtime. During a shut-in operation,
during which the well stops its original injection or production
operation, borehole pressure also changes due to the pressure
re-equilibrium process within the reservoir.
[0021] For wells that are hydraulically fractured, borehole
pressure changes can also induce mechanical strain perturbation in
the rock near the wellbore region. This is because of the
permeability difference between the hydraulic fractures and
reservoir rocks. Due to the low permeability within the hydraulic
fractures, the change of borehole pressure can propagate much
faster along the hydraulic fractures than into the formation rock
matrix. This can change the pressure difference between the fluid
within the fracture and the fluid in the pore space of the rock
matrix (pore pressure). This pressure difference variation can
change the fracture width, and can induce mechanical strain
variation in regions within and near the hydraulic fractures. If a
fiber is installed along the borehole, the mechanical strain
variation can be measured using the aforementioned DSS
technology.
[0022] One way of generating pressure-induced near-wellbore strain
changes is to shut-in a well that is under stable production.
During the stable production period, the pressure within the
hydraulic fractures that are connected to the wellbore is lower
than the pore pressure of the reservoir rock matrix. This pressure
difference drives the hydrocarbon resource to flow from the rock
matrix towards the borehole through the hydraulic fracture system.
After the shut-in operation, the pressure within the hydraulic
fractures increases to equalize with the rock matrix pore pressure,
and fracture width increases due to less pressure gradient between
the two.
[0023] FIG. 1 shows an illustrative process of using distributed
strain sensing to measure near-wellbore fracture geometry and
property due to borehole pressure changes. At least one sensing
fiber 202 is inserted into a wellbore 204. Pressure changes within
the wellbore 204 cause pressure changes at a hydraulic fracture 206
and perforation 208. As such, if the wellbore 204 pressure
increases during the monitoring period, the measured DSS signal is
expected to indicate a strong positive strain (extension) at the
borehole locations adjoining the near-wellbore fractures, and weak
negative strain nearby due to stress shadow effect (see Taghichian,
Zaman, and Devegowda 2014). The shape and the magnitude of the
strain signal are related to the geometry and property of
near-wellbore fractures and perforation cluster efficiency.
[0024] Illustrative methods in accordance with the present
disclosure can overcome difficulties associated with in-well DSS
measurement. There are several methods available to obtain strain
in a permanent casing conveyed sensing fiber:
[0025] (1) Utilizing DTSS technology to obtain the temperature
value and then subtracting the temperature effects from Brillouin
or Rayleigh frequency shifts. By this method, temperature spatial
resolution is generally more approximative than obtaining strain
data. In case of a sensing fiber in a metal tube, there is
typically no need to consider pressure effects.
[0026] (2) Utilizing a hybrid Rayleigh/Brillouin technology
developed by Kishida et al. (2014) to separate temperature and
strain in same sensing fiber. This method is generally able to keep
the same spatial resolution for temperature and strain, but the
precision is limited by Brillouin. The recently developed
Phase-Shift Pulse Brillouin Optical Time-Domain Reflectometry
(PSP-BOTDR) can provide enough resolution and precision. See
Shibata et al. (2017) and Nishiguchi et al. (2014).
[0027] (3) Utilizing a spatially designed cable that utilizes
different sensing fibers to separate strain, pressure and
temperature.
[0028] FIG. 2 shows an illustrative method 100 of determining
borehole characteristics. The method 100 includes arranging at
least one sensing fiber along a borehole, causing pressure changes
in the borehole, and measuring strain along the sensing fiber to
obtain strain data. In illustrative embodiments, the borehole along
which the sensing fiber is arranged has been fractured (e.g., but
not limited to, a naturally fractured borehole or a hydraulically
fractured borehole). In illustrative embodiments, the borehole
along which the sensing fiber is arranged is of a vertical producer
well or of a vertical injector well. In illustrative embodiments,
the borehole along which the sensing fiber is arranged is of a
conventional well.
[0029] An illustrative method 100 can be performed using a DPATS
(distributed pressure acoustic, temperature and strain) monitoring
system such as that disclosed in U.S. Pat. No. 9,829,352,
incorporated herein by reference in its entirety.
[0030] In illustrative methods, pressure changes in the borehole
can be caused by shutting-in the borehole, changing a choke size of
the borehole, and/or performing an injection in the borehole.
[0031] In illustrative methods, the measuring of strain along the
sensing fiber is performed before the pressure changes to obtain a
baseline strain reading, during pressure changes to obtain
time-dependent strain variation data, and after the pressure
changes to obtain strain recovery data. The strain data include the
baseline strain reading, the time-dependent strain variation data,
and the strain recovery data. In illustrative methods, the sensing
fiber is an optic fiber.
[0032] In illustrative methods, the measuring of strain along the
sensing fiber includes performing distributed strain sensing.
[0033] An illustrative method of determining borehole
characteristics further comprises determining borehole fracture
geometry based on the strain data.
[0034] An illustrative method of determining borehole
characteristics further comprises determining borehole perforation
efficiency based on the strain data.
[0035] An illustrative method of determining borehole
characteristics further comprises measuring temperature along the
sensing fiber to obtain temperature data.
[0036] An illustrative method of determining borehole
characteristics further comprises obtaining pressure data from the
borehole, and comparing the pressure data to the strain data to
obtain cluster performance data.
[0037] FIG. 3 shows the steps of an illustrative well operation and
data acquisition sequence to diagnose near-wellbore fracture and
perforation efficiency. At step 1, a wellbore reaches stable
production status, during which distributed strain sensing (DSS)
monitoring is OFF. At step 2, stable production continues for a
predetermined amount of time (e.g., but not limited to, 1-6 hours),
during which DSS monitoring is turned ON to obtain a baseline
strain measurement. At step 3, the wellbore is shut-in for a
predetermined amount of time, during which DSS monitoring is ON to
obtain time-dependent strain variation data. At step 4, the well is
reopened to resume stable production status, during which DSS
monitoring is ON to obtain strain recovery data. At step 5,
production continues, and DSS monitoring is turned OFF at the
completion of data acquisition.
[0038] Examples of strain data are graphed in FIGS. 4 and 5.
[0039] FIG. 4 shows an example of real field DSS measurement of
strain variation due to a shut-in operation on a
hydraulic-fractured oil producer. The temperature effects are
eliminated utilizing DTSS in this case. The well was in production
for more than a year after the hydraulic fracturing operation. A
well operation and DSS data acquisition similar to that set forth
in FIG. 3 were performed. The strain variation shown in FIG. 4 is
the strain difference between 70 hours after the shut-in (step 3)
and the stable flow period (step 2). Positive strain measurements
can indicate the existence of near-wellbore fractures, which
collocated with perforation clusters. The width of the positive
region can be related to the fracture zone geometry, and the height
and area can be linked to the amount of fracture width
increase.
[0040] FIG. 5 shows an example of the difference of magnitude of
positive strain observed at each perforation cluster location of an
unconventional well with two different hydraulic fracturing
designs. It can be observed that the difference of strain variation
at various perforation cluster locations of each design is
statistically significant, which illustrates the impact of
hydraulic fracturing designs on the near-wellbore fractures.
[0041] Illustrative methods of the present disclosure can have
various advantageous effects. Illustrative methods disclosed herein
can result in high-quality strain distribution results, and
effective near-wellbore strain measurements. Illustrative methods
disclosed herein can provide desirable spatial resolution and high
precision, so as to obtain useful information indicative of
perforation cluster performance. Illustrative methods disclosed
herein can provide non-intrusive processes which are easily
applicable to wells equipped with a sensing fiber indicative of
wellbore deformation. Illustrative methods disclosed herein can
estimate near-wellbore fracture geometry and properties from
measured strain signal by analyzing the shape and magnitude of the
strain response, as well as the temporal relation between the
strain signal and borehole pressure changes. Illustrative methods
disclosed herein can help compare different hydraulic fracturing
designs, which may impact near-wellbore hydraulic fracture
geometries and which can greatly affect production performance of
the well (see Lecampion et al. 2015). Illustrative methods
disclosed herein can help estimate perforation efficiency from the
strain variation measurements.
[0042] Moreover, for perforations or perforation clusters that are
not producing due to proppant screen out or other reasons, little
strain variation can be observed by the fiber near the perforation
because the connection between the borehole and reservoir is likely
lost. By examining the magnitude of strain variation at each
perforation location, perforation efficiency can be estimated more
effectively using illustrative methods disclosed herein.
Furthermore, in accordance with illustrative methods disclosed
herein, strain distribution of clusters can be monitored without
needing additional well operation--the production-induced pressure
depletion can instead be associated with long-term borehole strain
changes. The measurement of strain can be arranged during the
production life of the well, independently of other scheduled
events.
[0043] It will be appreciated by those skilled in the art that the
disclosure herein can be embodied in other specific forms without
departing from the spirit or essential characteristics thereof. The
presently-disclosed embodiments are therefore considered in all
respects to be illustrative and not restricted. The scope of the
invention is indicated by the appended claims rather than the
foregoing description and all changes that come within the meaning
and range and equivalence thereof are intended to be embraced
therein. The in-well pressure can be observed by separate pressure
and temperature sensors. If distributed an optical sensing cable is
used, the pressure and deformation relationship can be better
established even in distributed level.
REFERENCES
[0044] Baan, Mirko van der, Mirko van der Baan, David Eaton, and
Maurice Dusseault. 2013. "Microseismic Monitoring Developments in
Hydraulic Fracture Stimulation." Effective and Sustainable
Hydraulic Fracturing. [0045] Boone, K., R. Crickmore, Z. Werdeg, C.
Laing, and M. Molenaar. 2015. "Monitoring Hydraulic Fracturing
Operations Using Fiber-Optic Distributed Acoustic Sensing."
Unconventional Resources Technology Conference. [0046] Calvez, Joel
Herve Le, Joel Herve Le Calvez, Mike Eric Craven, Richard Caton
Klem, Jason David Baihly, Les A. Bennett, and Keith Brook. 2007.
"Real-Time Microseismic Monitoring of Hydraulic Fracture Treatment:
A Tool To Improve Completion and Reservoir Management." SPE
Hydraulic Fracturing Technology Conference. [0047] Curnow, Jennifer
S., and Azra N. Tutuncu. 2016. "A Coupled Geomechanics and Fluid
Flow Modeling Study for Hydraulic Fracture Design and Production
Optimization in an Eagle Ford Shale Oil Reservoir." SPE Hydraulic
Fracturing Technology Conference. [0048] Daniel Hill, A. 1990.
Production Logging: Theoretical and Interpretive Elements. Society
of Petroleum Engineers. [0049] Dong, Zhuo, and Shibin Tang. 2019.
"Numerical Study of near-Wellbore Hydraulic Fracture Propagation."
Theoretical and Applied Fracture Mechanics. [0050] Fallahzadeh,
Seyed Hassan, Md Mofazzal Hossain, Ashton James Cornwell, and
Vamegh Rasouli. 2017. "Near Wellbore Hydraulic Fracture Propagation
from Perforations in Tight Rocks: The Roles of Fracturing Fluid
Viscosity and Injection Rate." Energies 10 (3): 359. [0051]
Heddleston, Duncan Craig. 2009. "Horizontal-Well-Production Logging
Deployment and Measurement Techniques for US Land Shale Hydrocarbon
Plays." In. Society of Petroleum Engineers. [0052] Hong, Cheng-Yu,
Yi-Fan Zhang, Guo-Wei Li, Meng-Xi Zhang, and Zi-Xiong Liu. 2017.
"Recent Progress of Using Brillouin Distributed Fiber Optic Sensors
for Geotechnical Health Monitoring." Sensors and Actuators A:
Physical. [0053] Jin, Ge, Kyle Friehauf, Baishali Roy, Jesse J.
Constantine, Herbert W. Swan, Kyle R. Krueger, and Kevin T.
Raterman. 2019. "Fiber Optic Sensing-Based Production Logging
Methods for Low-Rate Oil Producers." Proceedings of the 7th
Unconventional Resources Technology Conference. [0054] Jin, Ge, and
Baishali Roy. 2017. "Hydraulic-Fracture Geometry Characterization
Using Low-Frequency DAS Signal." The Leading Edge. [0055] Kishida,
Kinzo, Yoshiaki Yamauchi, and Artur Guzik. 2014. "Study of Optical
Fibers Strain-Temperature Sensitivities Using Hybrid
Brillouin-Rayleigh System." Photonic Sensors 4 (1): 1-11. [0056]
Kurz, Bethany A., Darren D. Schmidt, and Philip E. Cortese. 2013.
"Investigation of Improved Conductivity and Proppant Applications
in the Bakken Formation." In. Society of Petroleum Engineers.
[0057] Maxwell, S. C., J. Rutledge, R. Jones, and M. Fehler. 2010.
"Petroleum Reservoir Characterization Using Downhole Microseismic
Monitoring." GEOPHYSICS. [0058] Miklashevskiy, D., V. Shako, I.
Borodin, V. Mukhin, R. Skochelyas, V. Shalamov, R. Valiullin, and
R. Iarullin. 2017. "New Production Logging Tool for Inflow
Profiling of Low-Rate Oil and Water Horizontal Wells: Case Studies
of Field Testing an Experimental Prototype." In. Society of
Petroleum Engineers. [0059] Nishiguchi, K. I., Li, C. H., Guzik, A.
and Kishida, K., 20104. Synthetic spectrum approach for Brillouin
optical time-domain reflectometry. Sensors, 14(3), pp. 4731-4754.
[0060] Ovchinnikov, Kirill, Andrey Gurianov, Pavel Buzin,
Aleksander Katashov, Oleg Dubnov, and Ruslan Agishev. 2017.
"Production Logging in Horizontal Wells without Well Intervention."
In. Society of Petroleum Engineers. [0061] Raterman, Kevin T.,
Helen E. Farrell, Oscar S. Mora, Aaron L. Janssen, Gustavo A.
Gomez, Seth Busetti, Jamie McEwen, et al. 2018. "Sampling a
Stimulated Rock Volume: An Eagle Ford Example." SPE Reservoir
Evaluation & Engineering. [0062] Shibata, R., Kasahara, H.,
Elias, L. P. and Horiguchi, T., 2017. Improving performance of
phase shift pulse BOTDR. IEICE Electronics Express, pp.
14-20170267. [0063] Seth, Puneet, Ripudaman Manchanda, Shuang
Zheng, Deepen Gala, and Mukul Sharma. 2019. "Poroelastic Pressure
Transient Analysis: A New Method for Interpretation of Pressure
Communication Between Wells During Hydraulic Fracturing." SPE
Hydraulic Fracturing Technology Conference and Exhibition. [0064]
Taghichian, A., M. Zaman, and D. Devegowda. 2014. "Stress Shadow
Size and Aperture of Hydraulic Fractures in Unconventional Shales."
Journal of Petroleum Science and Engineering. [0065] Ugueto,
Gustavo, Paul Huckabee, Magdalena Wojtaszek, Talib Daredia, and
Alan Reynolds. 2019. "New Near-Wellbore Insights from Fiber Optics
and Downhole Pressure Gauge Data." In. Society of Petroleum
Engineers. [0066] Webster, P., J. Wall, C. Perkins, and M.
Molenaar. 2013. "Micro-Seismic Detection Using Distributed Acoustic
Sensing." SEG Technical Program Expanded Abstracts 2013. [0067]
Zeng, F. H., and J. C. Guo. 2016. "Optimized Design and Use of
Induced Complex Fractures in Horizontal Wellbores of Tight Gas
Reservoirs." Rock Mechanics and Rock Engineering.
* * * * *