The optimal tight oil and shale gas development based on pre-existing fracture and principal stress
models: case study.
G.N. Erokhin* (Immanuel Kant Baltic Federal University), V.D. Baranov (TINP Ltd.), A.N. Kremlev (Immanuel Kant Baltic Federal University), S.V. Rodin (Anteloil Ltd.) & I.I. Smirnov (Immanuel Kant Baltic Federal University)
1
Gennady Erokhin
SEG Denver 2014
Objective: Optimal tight oil and shale gas development based on smart design of wellbore’s horizontal section for multistage hydraulic fracturing with the purpose to increase drainage area and decrease probability of accident
Objective Achievement: For smart design of wellbore’s horizontal section for multistage hydraulic fracturing we propose to use CSP Approach, which includes two methods:
FractureCSP - for mapping pre-existing fracture
MicroseismicCSP - for obtaining the principal stress axes before multistage hydraulic fracturing
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Outline
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I. Brief Description of the FractureCSP method - Mathematical statement; - FractureCSP Technology roadmap; - Case Studies
II. Brief Description of the MicroseismicCSP method -Mathematical statement;
- MicroseismicCSP Technology roadmap; - Case Studies
III. Optimal design of multistage hydraulic fracturing based on the pre-existing fracture information and on the principal stress axes information IV. Conclusions
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I. Brief description of the FractureCSP
method
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www.csp-amt.com 2D/3D CSP-PSTM
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FractureCSP (Common Scattering Point)
22 2
02
0
0
1
( , , ) , ?
t
uc a r u t r r
t
u
u t дано a r
Wave migration
FractureCSP is based upon: Russian mathematic school achievements in inverse problems of geophysics (academicians A.S. Alekseev, М.М.Lavrentiev, S.V. Goldin) Application of supercomputer technologies of overteraflop capacity
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Supercomputer technologies
Computing capacity:12 TFlops, RAM- 4 TB
CSP difractors cut
CSP-reflectors cut
Full wave field
99% 1%
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Diagram of seismic data processing
Conventional prestack migration methods
FractureCSP-prestack migration method
2D/3D seismic data
Time section/cube of CSP-
diffractors
2D/3D seismic data
Time section/cube of CSP-reflectors
Conventional time section/cube
Conventional processing FractureCSP processing
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FractureCSP processing
3D CSP-reflectors cub
Full wave
3D
2D
2D CSP-reflectors
3D CSP-diffractors cub
2D CSP-diffractors
95% energy
95% energy
5% energy
5% energy
100% energy
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The FractureCSP method resolution in the anticline flexure model
smV /20001
smV /20403
smV /20202
smVe /20151 smVe /20162 smVe /20173 smVe /20184 smVe /20195
Anticline flexure model
Conventional processing
FractureCSP processing
variation of velocity 0,1% ! SEG Denver 2014
Convectional technology of 2D data migration Ust-Balyk field. Bazhen formation (Tight oil)
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Sedimentary cover
Basement
Bazhenov fromation
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2D processing results, FractureCSP method. Ust-Balyk field. Bazhen formation (Tight oil)
Sedimentary cover
Bazhenov formation
Basement
Oil
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Cubes of CSP-reflectors and CSP-diffractors make a basis for conducting an attributive analysis traditional for the seismic survey. The results of attribute analysis of cubes are used for plotting the geological model of deposits, geological modeling, calculation of reserves and hydrodynamic modeling.
3D FractureCSP. Cubes of CSP-reflectors and CSP-diffractors
Software: 2D/3D CSP-PSTM
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Cubs of CSP-reflectors and CSP-diffractors
12 Video SEG Denver 2014
Tight oil. Bazhen formation diffractors map
Bazhen formation structural map
13 10 km
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Tight oil. Diffractors time section. Deformation zones in upper and lower layers
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Bazhen formation
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Tight oil. Map of prospective oil area based on the results of the cluster analysis
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Perspective areas
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Time section across western prospective area. Crossline 304
16 Reflectors Diffractors SEG Denver 2014
Time section across western prospective area. Inline78
17 Reflectors Diffractors SEG Denver 2014
Western prospective area recommended for drilling
wells
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Cluster map Diffractors
Pre-existing fracture map. Tight oil - Bazhen formation. Western
prospective area
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II. Brief description of the MicroseismicCSP method
19 www.csp-amt.com
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What the MicroseismicCSP is based on?
• Mathematical results for inverse source problem – “Seismic Moment Tensor Inverse Problem” (Erokhin G. etc. 1987, Anikonov Y. etc. 1997)
• Parallel Supercomputing Processing (Erokhin G. etc. 2002)
• Small Surface Microseismic Acquisition System (Erokhin G. etc. 2007, 2008)
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Mathematical Statement of Seismic Moment Tensor Inverse Problem (SMTIP )
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The core of technology is digital processing of data of microseismic surface monitoring of subsurface
events which is based on mathematical algorithms for inversion of determining the right-hand side of
the Lame's differential equation system (G.N. Erokhin, P.B. Bortnikov 1987; Anikonov Yu.E. etc. 1997;
G.N.Erokhin etc. 2002):
)1(),(0
2
2
txxt
u
xij
j
i
j
ij
Here ;;,,3,2,1, 13 RtRyxji - the medium density, ij - the stress tensor related to the
displacement vector ),,(),( 321 uuutxu in the form of
)2()(k
kij
i
j
j
iij
x
u
x
u
x
u
where , - are the Lame constants and the repetition of indices mean summation and ),(0
txij - the
stress tensor of the crack which is of the form
)3()()(0 yxtM ijij ,
where 33,2,1, Ryji , )(x - is Dirak function of order zero,
)t(M ij - symmetric tensor of
second order. )t(M ij is called the seismic moment tensor. The tensor
)t(M ij has dimension of units
of energy measurement )( 12 scmg . The distribution dimension )(x - 3/1 sm . The vector y
describes the coordinates of the earthquake source.
Let the parameter 0t characterize the time of process beginning in the source )tt,0)t(M( 0ij . Let
us also suppose that , and - are the known constants. SEG Denver 2014
Mathematical Statement of Seismic Moment Tensor Inverse Problem (continued)
The inverse problem is in the determination of the parameters yt ,0 and the symmetrical tensor
)(tM ij
from the data of the form
( ) ( , ) ( ), 4. (4)k k kv t u x t t k
Here kk Rx ,3 - is the noise of normal distribution, the zero mean value and some known covariance
matrix ),( 'kk xxG .
Determination of the parameters yt ,0 - is the essence of the kinematic inversion. The kinematic
inversion allows us to determine spatial location of microseismic emission sources and the time of the
process beginning The algorithm of determining the kinematic parameters of sources is described in
the patent (G.N. Erokhin et al. 2008).
Determination of the tensor components )(tM ij - is the essence of dynamic inversion.
To solve both the kinematic inverse problem and its dynamic part, the high level software system using
super computer parallel computing has been developed.
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Solution control. Creating the optimal algorithm for the inverse problem
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Small Surface Microseismic Acquisition System
Acquisition scheme. The blue curve
shows the wellbore path.
Triangles - the location of the sensors
with the numbers
Scheme of Small Surface Microseismic Acquisition System.
The vertical geophones GS-11D or similar are located on 1-3 m depth. Aperture diameter is about 800 m. The number of sensors equals 30-60 units . Coordinates of each sensor in the aperture are calculated with high precision on the basis of GPS. Data sampling is not more than 2 ms. Optimum depths for monitoring in this case are in the range of 2-4 km. Assumption that event time duration is not more that 50 ms.
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Kinematic and Dynamic parts of SMTIP The results of Kinematic stage of the inverse problem solution are four parameters : three coordinates of the event and its beginning time. The results of Dynamic stage of the inverse problem solution are six components of Seismic Moment Tensor, which depend on time. Determination of the components is based on the minimization the functional (5) based on the minimization method in equations (6)-(9). (Erokhin G. and P. Bortnikov, 1987, Anikonov Y.etc., 1997, Erokhin G. etc., 2002))
3D visualization of Seismic Moment Tensor in principal stress axes during time event
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Microseismic events distribution with 3D visualization of seismic moment tensor on principal stress axes
Grid step – 50 м 26 SEG Denver 2014
Microseismic events distribution with 3D visualization of seismic moment tensor in components DС-CLVD-ISO
71.4%
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Double-Couple (DC)
Compensated Linear Vector Dipole (CLVD)
Isotropic (ISO)
19.7 % 8.9 %
MicroseismicCSP roadmap
Stages: • Array design and installation of acquisition system • Registration of the noise and perforation shots (calibration) • Surface registration of microseismic data caused by
microseismic events • Preliminary data processing • Solution of the kinematic and dynamic parts of SMTIP • Interpretation of the results
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Well down
Perforation. Well #4431, West Siberia
Well#4431 Image of seismic emission for perforation in horizontal plane. Аccuracy is 10 meters or better. Malobalikskoe oilfield. Well cluster #604, well#4431. The depth is 2760 meters. 2006, Ugra.
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The Schemes Examples and MicoseismicCSP Features of Acquisition Systems
Features:
• Small size of aperture ( 0,2 sq. km)
• High density of sensors: 200 sen./sq. km.
• Data sampling under 1 ms.
• Possibility of long duration observation ( more 2 weeks).
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“Oimasha” oilfield
“Ashiagar” oilfield
“Alatube” oilfield
“Srediy Nazim” oilfield
“Uzen” oilfield
“Nazim” oilfield
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List of problems solved by MicroseimicCSP Technology
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1. Monitoring of hydraulic fracturing
2. Control of waterflooding
3. Estimation of ports productivity after multistage hydraulic fracturing
4. Estimation of area of oil sources of deposits (drainage area)
5. Oilfield fault-block structure mapping SEG Denver 2014
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Case study #1: Hydraulic Fracturing. Source mechanism. Directions of the principal stress axes
Oilfield West-Malobalikskoe. Cluster well #605, well #5538. 2007, Ugra
Max horizontal stress
Min horizontal stress
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Video layer
Case study #2: Hydraulic Fracturing. Mapping of water filtration in channels during hydraulic fracturing
33 Oilfield Prirazlomnoe. Cluster well #143, well 6642, depth 2640, Ugra, 2005 SEG Denver 2014
Case study #3: Multistage Fracturing
Layout of surface sensors. Oilfield Vientoskoe, cluster well #11, well #634G, 2013, Ugra 34 SEG Denver 2014
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Space image of Priobskoe oilfield. Projection of well № 16502, sources of seismic emission and sensors on the day surface. Depth 2403. Ugra, 2010.
Case study #4: Waterflooding. Monitoring of front displacement during fluid injection in the layer
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Case study #4: Waterflooding. Distribution of flooding, in accordance with the extension of the seismic emission zone . Step - 100 hours
36 Top view (center), east view (right) and north view (bottom)
of the microseismic cloud (A) 100 hr, (B) 200 hr, (С) 300 hr,
(D) 400 hr, (E) 500 hr, (F) 600 hr after the start of the injection
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Geometry of the surface receiver array, wells. Deposit Lebyazhye. The depth is 2680 meters. Red cross – sensors. The period of monitoring is 30 days. 2006, Ugra.
well 312
well
301
well 311
wells 1007, 1009
well 1005
Case study #5: Estimation of drainage area of deposits . The layout of surface sensors and oil wells. Acquisition time – 30 days
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Case study #5: Estimation of drainage area of deposits. Results of microseismic monitoring at the depth 2680 meters. Acquisition time– 30 days
Oilfield Lebyazhye, 2006, Ugra SEG Denver 2014
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Case study #6: Estimation of ports productivity after multistage hydraulic fracturing
3D image of microseismic monitoring of multistage fracturing. Well 100G. Grid step 50m. Oilfield Srednenazimskay. Depth – 2700 m. West Siberia, 2013
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Case study #6: Estimation of ports productivity after multistage hydraulic fracturing. Long-duration passive microseismic monitoring
3D image of the long-duration passive microseismic monitoring after multistage fracturing. Grid step 50m. Well 100G. Oilfield Srednenazimskay. West Siberia, 2013
1 day 2 day … … 13 day 14 day
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Case study #6: Estimation of ports productivity after multistage hydraulic fracturing
3D image of microseismic monitoring of multistage fracturing with fault-block structure mapping. Well 100G, 70 ton/day. Grid step 50m. Oilfield Srednenazimskay. West Siberia, 2013
Port #5 with maximum oil influence
Results were confirmed by oil influence researches in the well
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Case study #7: Oilfield fault-block structure mapping. 3D view of microseismic events near bottom-hole. Long-duration passive monitoring
42 Oilfield Atambay-Sertube, well #5, Kazakhstan, 2012
400 m
400 m
Planes of faults were designed with IHS Kingdom package SEG Denver 2014
Case study #7: Oilfield fault-block structure mapping. 3D view of microseismic events near bottom-hole
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Oilfield Atambay-Sertube, well #5, Kazakhstan, 2012
Video SEG Denver 2014
III. Optimal design of multistage hydraulic fracturing based on the
information of pre-existing fracture and principal stress axes
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www.csp-amt.com SEG Denver 2014
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Information of pre-existing fracture zone in the Bazhen formation. West perspective area. Case of obvious topology
Quantitative estimation of Diffractivity Density (DD). DD along the horizontal section of wellbore versus Gas
Diffractivity Density
Correlation between average value of DD and average value of Gas along the horizontal section of wellbore
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Optimal design trajectory of horizontal section of a wellbore based on the information of pre-existing fracture
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FractureCSP roadmap: 1. FractureCSP processing based on 3D CSP-
PSTM. Obtaining the 3D CSP-diffractors cube in SEG-Y format.
2. Design of a set of admissible trajectories of horizontal section of a wellbore
3. Calculation the Diffractivity Density along the each probable trajectory
4. Search the optimal trajectory of wellbore for multistage hydraulic fracturing with the maximum value of Diffractivity Density (yellow color – 467 units of DD sum along the section)
5. Microseismic monitoring multistage fracturing with estimation of ports productivity after fracturing based on MicroseismicCSP Technology Tight oil. Bazhen formation diffractivity map Oilfield Vientoskoe, cluster well #11, well #634G, 2013, Ugra
Horizontal section
Vertical section
Diffractivity density curves
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Design horizontal section of wellbore for some multistage hydraulic fracturing along the pre-existing fracture zone
`
`
`
`
Main strain axes
Wellhead
X
Y α
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Probability of accident when α small
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Optimal design based on the information of principal stress axes
Depth - 2766 meters. Grid size - 100х100 meters. Red/blue – maximum/minimum stress axes at the seismic emission points. The curved line - projection of a well borehole. Green triangles - geophones
Max horizontal stress
Min horizontal stress
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Design horizontal section of wellbore for some multistage hydraulic fracturing along the minimum strain
`
`
`
`
Main strain axes
Wellhead
Y
X 50
α
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IV. Conclusions
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1. Optimal tight oil and shale gas development based on CSP Approach assumes simultaneous use of the following two methods :
FractureCSP - for mapping pre-existing fracture
MicroseismicCSP- for obtaining the principal stress axes during microseismic monitoring of hydraulic fracturing
2. Models of pre-existing fracture zone and principal stress axes are used to design the optimal well trajectory with the purpose to increase drainage area and to decrease probability of accident
3. Application of suggested CSP Approach can significantly reduce cost of development of tight oil and shale gas and will increase safety of works
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WWW.CSP-AMT.COM
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Thank you for your attention!
Immanuel Kant Baltic Federal University
«Technologies of inverse problems»
«Anteloil»
54 SEG Denver 2014
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