Evaluation of CO2 enhanced oil recovery and sequestration potential in low permeability reservoirs, Yanchang Oilfield, China

Journal of the Energy Institute 87 (2014) 306e313

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Journal of the Energy Institute journal homepage: http://www.journals.elsevier.com/journal-of-the-energyinstitute

Evaluation of CO2 enhanced oil recovery and sequestration potential in low permeability reservoirs, Yanchang Oilfield, China D.F. Zhao a, *, X.W. Liao a, D.D. Yin b a b

MOE Key Laboratory of Petroleum Engineering, China University of Petroleum (Beijing), Beijing, China EOR Research Institute, China University of Petroleum (Beijing), Beijing, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 13 February 2014 Received in revised form 3 March 2014 Accepted 25 March 2014 Available online 12 June 2014

Sequestrating CO2 in reservoirs can substantially enhance oil recovery and effectively reduce greenhouse gas emission. To evaluate the potential of CO2 enhanced oil recovery (EOR) and sequestration for Yanchang Oilfield in China, a screening standard which was suitable for CO2-EOR and sequestration in Yanchang Oilfield was proposed based on its characteristics of strong heterogeneity, high water content and severe fluid channeling after water flooding. In addition, an efficient calculation method e stream tube simulation method was presented to figure out CO2 sequestration coefficient and oil recovery factor. After screening and evaluating, it turned out that 148 out of 176 blocks in 22 oilfields were suitable for CO2-EOR and sequestration. CO2 flooding after water flooding can produce 180.21
106 t more crude oil and sequestrate 223.38
106 t CO2. The average incremental oil recovery rate of miscible reservoirs was 12.49% and the average CO2 sequestration coefficient was 0.27 t/t while the two values were 6.83% and 0.18 t/t for immiscible reservoirs. There are comparatively more reservoirs that are suitable for CO2-EOR and sequestration in Yanchang Oilfield than normal, which can obviously enhance oil recovery and means a great potential for CO2 sequestration. CO2-EOR and sequestration in Yanchang Oilfield has a bright application prospect. © 2014 Energy Institute. Published by Elsevier Ltd. All rights reserved.

Keywords: CO2 sequestration Enhanced oil recovery Capacity estimation CO2 EOR screening China oil reservoirs

1. Introduction Greenhouse gas reduction and energy demand are two significant problems confronting the economic development in China. Sequestrating CO2 in reservoirs can not only enhance oil recovery drastically, but also be able to reduce CO2 emission effectively [1]. Sequestrating CO2 in reservoirs is one of the most effective ways to sequestrate CO2. Because compared with saline layer, reservoir reserve has been known, a large amount of reservoir data has been acquired and the injection equipment has already been built [2,3]. During the evaluation of CO2-EOR and sequestration, it is of paramount importance to screen the reservoirs. Daniel, D. and Taber, J.J. et al. [4,5] concluded screening criteria of CO2 flooding on the analysis of successful field application. Bradshaw J. et al. [1,6e8] also suggested screening parameters over previous researches and ranked candidate reservoirs by setting optimum value and parametric weight, which proved ideal application in Alberta reservoirs. For most of the oilfields in China, reservoir forming materials are continental sedimentation with their crude oil to be high viscosity, high paraffin content, high freezing point and reservoirs having complex structure and strong heterogeneity. Besides, among all these reservoirs, low permeability reservoirs (or tight reservoirs) and reservoirs with high temperature and high salinity account for a sizeable percentage, and most oilfields have fluid channeling after a long-term water flooding [9]. Zhang Liang et al. [10e12] conducted a research into the screening standard for enhancing oil recovery through CO2 flooding and put forward a screening standard suitable for CO2-EOR and sequestration in China oilfields. Based on this research and combined with the characteristics of Yanchang Oilfield, this paper presented a screening standard for CO2-EOR and sequestration for Yanchang Oilfield. There are four kinds of CO2 sequestration capacity: theoretical sequestration capacity, effective sequestration capacity, practical sequestration capacity and matched sequestration capacity [2,3], among which theoretical sequestration capacity and effective sequestration capacity are two concerning values. Theoretical sequestration capacity presented by Carbon Sequestration Leadership Forum (CSLF)

* Corresponding author. E-mail address: [email protected] (D.F. Zhao). http://dx.doi.org/10.1016/j.joei.2014.03.031 1743-9671/© 2014 Energy Institute. Published by Elsevier Ltd. All rights reserved.

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suits the theory well [6], but it had not taken CO2 resolved in the water and oil into consideration. As most reservoirs in China are high watercut reservoirs, theoretical sequestration capacity considering CO2 resolved in water and oil was presented by Shen Pingping and Liao Xinwei [4,13]. Effective sequestration capacity is a subset of theoretical storage capacity and it considers factors like reservoir property, sealing capacity of reservoir, burial depth, reservoir pressure system, pore volume, etc [1]. CSLF presented a calculation method for effective sequestration capacity based on material equilibrium method, and this method has taken a lot of factors into account, such as buoyancy, gravity override, mobility ratio, heterogeneity, water saturation, aquifer strength, etc [2]. These effective storage coefficients are hard to determine, and only through numerical simulation method can these data be obtained. Personnel from related organizations and countries like USA and EU raised analogy method to calculate CO2 sequestration capacity in the CO2-EOR program. This method obtained effective sequestration capacity through introducing CO2 utilization coefficient [2,3,14,15]. However, CO2 utilization coefficient fluctuated strongly, so the sequestration coefficient was introduced in this paper to better reflect the variation tendency of CO2 sequestration capacity. To figure out the recovery factor and sequestration coefficient is the key to study the assessment of CO2-EOR and sequestration potential, and the project data of EOR or numerical simulation are usually used. However, it is obviously unsuitable to carry out preliminary CO2-EOR and sequestration appraisal in large scale, so a reliable and efficient stream tube simulation method based on fractional flow theory was proposed in this paper. This paper put forward a screening standard that was suitable for CO2-EOR and sequestration in Yanchang Oilfield, and introduced sequestration coefficient to better reflect the variation tendency of CO2 sequestration capacity. Besides, based on fractional flow theory, stream tube simulation method was proposed to efficiently calculate CO2 sequestration coefficient and recovery coefficient, and numerical simulation method was used to verify the values so as to ensure that the deviation was within acceptable range. Finally, stream tube simulation method was used to evaluate the potential of CO2-EOR and geological sequestration through miscible flooding and immiscible flooding respectively. The results states that there is a great potential of conducting CO2-EOR and sequestration in Yanchang Oilfield and the technique has a bright application prospect there.

2. Procedure 2.1. Screening standard for CO2-EOR and sequestration Based on some former researches and through the utilization of the reservoir data of Yanchang Oilfield, typical models were established to analyze the effect law of each parameter on the oil recovery and storage capacity as well as the sensibility of each parameter. A comprehensive appraisal standard for CO2-EOR and sequestration in Yanchang Oilfield was proposed by using fuzzy comprehensive evaluation and analytic hierarchy process methods in this paper [16,17], as shown in Table 1.

2.2. Calculation method of theoretical sequestration capacity In high water cut reservoir, CO2 theoretical sequestration capacity includes three parts, theoretical sequestration capacity in free space of oil reservoir, theoretical sequestration capacity dissolving in water and theoretical sequestration capacity dissolving in oil [2,3].

MCO2 t ¼ MCO2 MCO2

displace

displace

þ MCO2

in oil

þ MCO2

(1)

in water

h i ¼ rCO2 r Rf
POIP  Viw þ Vpw

(2)

Table 1 Screening standard for CO2-EOR and sequestration in Yanchang Oilfield. First class index

Weight coefficient of first class index

Second class index

Weight coefficient of second class index

The worst value

The optimal value

Reservoir characters

0.65

Sedimentary rhythm The initial oil saturation (%) Reservoir effective thickness (m) Depth of the reservoir pressure (m) Average reservoir permeability (103 mm2)

0.16 0.16 0.16 0.16 0.10

Positive 0.65 1 2500 1.5

Interlayer development situation (KV/KH) Heterogeneity (coefficient of variation) Formation dip angle Directional permeability (KY/Kx) The temperature Fluid density Fluid viscosity Well pattern Well spacing (m)

0.10 0.06 0.04 0.04 0.02 0.5 0.5 0.5 0.5

Reverse 0.3 30 300 0.1 100 0.5 0.7 5 100 75 1000 1000 Seven spot 400

Fluid properties

0.25

Development factors

0.1

Calculation method of theoretical sequestration capacity and effective sequestration capacity.

0.001 0.1 35 5 19 700 1 Inverted nine spot 100

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0.16 CO2 sequestra on coefficient

0.14 0.12 0.1 0.08 0.06

planar heterogeneity=0.00

0.04

planar heterogeneity=0.17

0.02

planar heterogeneity=0.33

0 0

0.5

1

1.5

2

2.5

Plane heterogeneity Fig. 1. Impact of plane heterogeneity on sequestration coefficient.

MCO2

in water

MCO2

in oil

  ¼ Ef
rCO2 r
PWIP þ Viw  Vpw
mCO2

  ¼ Ef
rCO2 r
POIP
1  Rf
mCO2

(3)

in water

(4)

in oil

in which, MCO2 t is the theoretical sequestration capacity, 106 t; MCO2 displace is sequestration capacity in the process of CO2 flooding, 106 t; MCO2 in oil is sequestration capacity of CO2 dissolved in the reservoir water, 106 t; MCO2 in water is sequestration capacity of CO2 dissolved in crude oil, 106 t; POIP is the amount of oil in the reservoir after water flooding, 106 t; PWIP is the amount of water in the reservoir after water flooding, 106 t; Ef is sweep efficiency of CO2 displacement; mCO2 in water is the solubility of CO2 in water; mCO2 in oil is the solubility of CO2 in oil. As CO2 can only dissolve in oil and water by directly contacting, CO2 swept coefficient was introduced when the storage volumes that CO2 dissolved in water and oil were calculated. 2.3. Calculation method of effective sequestration capacity Effective sequestration capacity is a subset of theoretical sequestration capacity. So based on theoretical sequestration capacity, CSLF proposed a calculation method to work out effective sequestration capacity with factors like buoyancy, gravity override, mobility ratio, heterogeneity, water saturation, aquifer strength been taken into consideration [2,3].

MCO2 e ¼ Ce
MCO2 t ¼ Cm
Cb
Ch
Cw
Ca
MCO2 t

(5)

in which, MCO2 e is the effective sequestration capacity, 106 t; Ce is comprehensive influence coefficient of the effective sequestration of various factors; Cm is the effective sequestration coefficient caused by mobility influence; Cb is the effective sequestration coefficient caused by buoyancy influence; Ch is the effective sequestration coefficient caused by heterogeneity influence; Cw is the effective sequestration coefficient caused by water saturation influence; Ca is the effective sequestration coefficient caused by aquifer strength influence. The calculation coefficients of this method are hard to determine, and effective sequestration coefficients are usually determined through numerical simulation. CO2 utilization coefficient (utilization coefficient ¼ total storage capacity/accumulated oil production) is wildly used in USA and European countries to evaluate CO2 sequestration capacity [2,3]. However, the CO2 utilization coefficient ðRCO2 Þ has relative large amplitude (about 0.1e0.8 t/bb), so it cannot better illustrate the variation tendency of CO2 sequestration. To solve this problem, a concept of

1.6 CO2 sequestra on coefficient

1.4 1.2 1 0.8 0.6

diffusion coefficient=0.000m^2/d

0.4

diffusion coefficient=0.002m^2/d

0.2

diffusion coefficient=0.005m^2/d

0 0

0.5

1

1.5

2

Molecular diffusion Fig. 2. Impact of molecular diffusion on sequestration coefficient.

2.5

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Table 2 PVT and MMP observation of well C-1. Reservoir conditions Initial formation pressure Initial formation temperature

17.1 MPa 70.26  C

Formation fluid properties Fluid type Saturation pressure (70.26  C) Formation volume factor (70.26  C, 17.1 MPa) Initial density (70.26  C, 17.1 MPa) Viscosity (70.26  C, 17.1 MPa) Tank oil (0.101 MPa, 20  C) MMP (70.26  C)

Black oil 5.59 MPa 1.1365 0.7762 g/cm3 1.62 mPa s 0.8325 g/cm3 18.4 MPa

Fluid components mole fraction C1 þ N2 CO2 þ C2 e C10 C11þ

18.53% 38.01% 43.46%

CO2 sequestration coefficient (¼total storage capacity/oil geological reserve) was introduced. As shown in Figs. 1 and 2, along with the increase of planar heterogeneity, the sequestration coefficient SCO2 was on a declining curve, and along with the increase of diffusion coefficient, sequestration coefficient showed an increase trend. Therefore, here came a conclusion e as the variation range can be known directly from the value of SCO2 , CO2 sequestration coefficient SCO2 could better convey the variation tendency of CO2 sequestration capacity. By applying Equations (1)e(5), the efficient sequestration capacity can be given by

SCO2 ¼ Ce


h

 i ð1  Sw Þ
Rf þ Sw
Rw þ Ef
Spw
ð1  Rw Þ
mCO2

in water

  þ Ef
1  Spw
ð1  Rw Þ
mCO2

in oil

(6)

in which, SCO2 is the sequestration factor; Sw is the initial water saturation, %; Spw is the present water saturation, %; Rw is the water recovery factor, %.

2.4. Calculation of recovery factor (R) and sequestration coefficient Two key parameters were involved in CO2-EOR and sequestration appraisal: recovery factor (R) and sequestration coefficient ðSCO2 Þ. The two parameters must be determined before the evaluation, and numerical simulation is the best way to do this job. However, for now, commercial software like Eclipse and CMG all need detailed data of the oilfield for real calculation and take a long time, which is obviously unsuitable to apply for a large number of oilfields during a short time. Therefore, efficient stream tube simulation method was presented in this paper to determine R and SCO2 . Stream tube simulation method is based on fractional flow theory and with key factors like viscous fingering, vertical heterogeneity, gravitational separation and miscible effect being taken into account. The assumption conditions for the model are: ① oil and gas will not volatilize to gas-phase during the flow process; ② displacement is a constant temperature process; ③ Koval coefficient is used to depict viscous fingering; ④ when the injection mode is water-gas alternate, water and CO2 will be injected with a certain WAG ratio simultaneously; ⑤ there's no free gas in miscible flooding; ⑥ there's no big fracture in the reservoir and no leak during CO2 injection. According to the law of conservation of mass, the relation equation of component concentration and fractional flux was obtained:

vCi vF þ i ¼0 vtD vXD

(7)

Z t in which, i ¼ 1dthe water components; i ¼ 2dthe oil components; i ¼ 3dthe injected gas components; XD ¼ X/Ldthe dimensionless distance of the system; tD ¼ qdt=dVp ddimensionless time in the pores; Cidthe overall concentration of component. 0

Ci ¼ Ci1 S1 þ Ci2 S2 þ Ci3 S3 ; Fi ¼ Ci1 f1 þ Ci2 f2 þ Ci3 f3 ;

i ¼ 1; 2; 3

(8)

i ¼ 1; 2; 3

(9)

in which, Cijdthe concentration of component i in the j phase. According to the assumptions that the oil and water do not evaporate into the gas phase, So, in the above formula, C33 ¼ 1, C13¼C23 ¼ 0. j ¼ 1dthe water phase; j ¼ 2dthe oil phase; j ¼ 3dthe gas phase; Sjdthe saturation of the j phase; fjdthe fractional flow of the j phase. The model above is immiscible model, for miscible model, the Ci3S3 in Equation (2) will be 0, Ci3f3 in Equation (3) will be 0, and i ¼ 1,2. Table 3 Scenario design in Chuan 72 block. Scenario

Injection rate

Cumulative injected volume

Production period (year)

Water flooding CO2 flooding

35 m3 12,000 m3

0.6PV 0.6PV

20 20

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D.F. Zhao et al. / Journal of the Energy Institute 87 (2014) 306e313

Table 4 Prediction results of Chuan 72 block. Methods

Recovery factor after water flooding

Recovery factor after CO2 flooding

Recovery increment

Sequestration coefficient

Numerical simulation Stream tube simulation

20.7 21.9

28.8 30.6

8.1 8.7

0.261 0.228

In the model, the breakthrough time of injected gas and oil recovery were calculated by revised fractional flow theory, which had considered the effect of factors like viscous fingering, volume swept coefficient, vertical heterogeneity and gravity segregation. Finally, characteristics method was used to solve the model. Koval coefficient was used in the model to depict the effects that factors like viscous fingering and vertical heterogeneity have on fractional flow. As the density of injected gas was lower than oil and water, injected gas had a trend to move toward the top of oil layer and override or slip stream at relative lower part in the oil layer. According to that, Koval enlargement method was used in the model to amend the effect of gravity. The model transformed two-dimension planar displacement calculation into one-dimension displacement calculation through stream tube simulation based on fractional flow theory so as to obtain relative precise and efficient seepage calculation model. This model can be used to evaluate the breakthrough time of oil-gas front, oil recovery, geological sequestration coefficient, etc. The parameters need to be inputted for fractional flow theory includes porosity, permeability, saturation, oil viscosity, oil density, relative permeability, well pattern type, injection mode, injection time, etc. This method can evaluate the sequestration coefficient and oil recovery reliably and quickly. 2.5. Determination of the minimum miscible pressure Before the appraisal of CO2-EOR and geological sequestration, the minimum miscible pressure (MMP) of the target reservoir needs to be determined first to make sure that whether miscible state is realizable or not. This paper combined the experimental results of slim tube test with the NPC empirical formulas method of United States Department of Energy (USDOE) e reservoir temperature and molecular weight C5þ in the crude oil were used to evaluate MMP so as to meet the demand of being both accurate and efficient. Below is MMP calculation model suitable for Yanchang Oilfield.

  MMP ¼ 329:558 þ 7:727
MW
1:005T  4:377
MW  MW ¼

(10)

 1 8864:9 1:012 G

(11)

in which, MWdmolecular weight of C5þ; MMPdminimum miscible pressure, Psi; Tdreservoir temperature,  F; Gdgravity of tank oil, API. 3. Results and conclusion The method was tested through its application to two synthetic fields and then to a real field in Yanchang Oilfield. The results of these applications are presented and discussed in this section. 3.1. Synthetic fields 3.1.1. Chuan 72 block PVT test and slime tube observation have been taken for Chang 61 in Chuang 72 block, and the fluid properties are shown in Table 2. The initial formation pressure was 17.1 MPa, which was lower than MMP (18.4 MPa), and the CO2 displacement was immiscible flooding. The model was inverted nine-point well network, and the well spacing and array pitch were 340
150 m. Geological parameters of each grid Table 5 PVT and MMP observation of well F-5. Reservoir conditions Initial formation pressure Initial formation temperature

20.6 MPa 84.52  C

Formation fluid properties Fluid type Saturation pressure (84.52  C) Formation volume factor (84.52  C, 18.0 MPa) Initial density (84.52  C, 18.0 Mpa) Viscosity (84.52  C, 18.0 Mpa) Tank oil (0.101 MPa, 20) MMP (84.52  C)

Black oil 9.21 MPa 1.1286 0.7332 g/cm3 1.31 m Pa s 0.8303 g/cm3 18.9 MPa

Fluid components mole fraction C1 þ N2 CO2 þ C2 e C10 C11þ

25.26% 39.35% 35.39%

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Table 6 Scenario design in Fang 5 block. Scenario

Injection rate

Cumulative injected volume

Production period (year)

Water flooding CO2 flooding

38 m3 12,000 m3

0.6PV 0.6PV

20 20

like permeability and porosity were obtained through Kriging interpolation method according to the values around the well. The main parameters are as follows: the gridding dimension of geological model was 27
16
3; the gridding size was 30 m(X)
30 m(Y)
4.5 m(Z); the variation range of reservoir permeability was 0.1e0.9 mD with its average value to be 0.54 mD; the porosity variation range was 11.31%e 13.25% with its average value to be 12.42%; the immobile water saturation was 36.86%; the average thickness of sand body and production layer were 16.8 m and 13.6 m respectively. The injection velocities of water and CO2 were both 35 m [3]/d (under reservoir condition), and the flowing bottom hole pressure was about 9 MPa (Table 3). Through the two methods above, the total volume of produced oil and CO2 sequestration capacity during CO2 flooding after water flooding were predicted, as shown in Table 4. Through CO2 flooding, 8.7% more oil will be produced and the sequestration coefficient was 0.228. 3.1.2. Fang 5 block For another typical block, PVT test and slime tube observation have been taken for Chang 8 in Fang 5 block, and the fluid properties are shown in Table 5. The initial formation pressure was 20.6 MPa, which was lower than MMP (18.9 MPa), and the CO2 displacement was immiscible flooding. The model was inverted nine-point well network, and the well spacing and array pitch were 420
140 m. Geological parameters of each grid like permeability and porosity were obtained through Kriging interpolation method according to the values around the well. The main parameters are as follows: the gridding dimension of geological model was 29
38
3; the gridding size was 30 m(X)
30 m(Y)
3 m(Z); the variation range of reservoir permeability was 0.1e0.7 mD with its average value to be 0.41 mD; the porosity variation range was 6.3%e 11.4% with its average value to be 10.2%; the immobile water saturation was 37.61%; the average thickness of sand body and production layer were 14.2 m and 11.2 m respectively. The injection velocities of water and CO2 were both 38 m [3]/d (under reservoir condition), and the flowing bottom hole pressure was about 10 MPa (Table 6). Through the two methods above, the total volume of produced oil and CO2 sequestration capacity during CO2 flooding after water flooding were predicted, as shown in Table 7. Through CO2 flooding, 12.6% more oil will be produced and the sequestration coefficient was 0.235. A comparison between the results of stream tube simulation appraisal method and numerical simulation method stated that the oil recovery and geological sequestration coefficient calculated by stream tube simulation method were a little bigger. This is because that stream tube simulation method has left factors like capillary force out of consideration. However, the deviation was acceptable, so the stream tube simulation method could still be applied for the evaluation of CO2-EOR and geological sequestration potential.

3.2. Real field in Yanchang Oilfield Yanchang Oilfield reservoir has an 2100 m average depth, 15.1 MPa average formation pressure, and 70.6  C average formation temperature. It is a normal warm-pressing system. Viscosity of the formation oil is 0.32e11.5 mPa s, and the range of oil saturation is 46%e72%. Screening standard for CO2-EOR and sequestration mentioned before in this paper was adopted to carry out appraisal calculation for the reservoir suitability of CO2 flooding in 174 blocks from Yanchang Oilfield, and then all the appraisal values of all the blocks were ranked. 0.53 was used as the boundary for the evaluation of Yanchang Oilfield. The detailed statistics are exhibited in Tables 8 and 9. Among the 176 blocks, there are 148 blocks that were suitable for CO2-EOR and sequestration, which accounted for 84% of all the oilfield blocks and possessed 80% geological reserves of Yanchang Oilfield. Miscible flooding and immiscible flooding potential evaluations were also conducted for some appropriate reservoirs using the CO2-EOR and sequestration appraisal method studied above, and the results were shown in Tables 10 and 11. As shown in Tables 10 and 11, 148 blocks in Yanchang Oilfield were suitable for CO2-EOR and sequestration. CO2 flooding after water flooding can produce 180.21
106 t more crude oil and sequestrate 223.38
106 t CO2. The average incremental oil recovery rate of miscible reservoirs (65 blocks) was 12.49% and the average CO2 sequestration coefficient was 0.27 t/t while the two values were 6.83% and 0.18 t/t for immiscible reservoirs (83 blocks). Crude oil increased 129.42
106 t and sequestrated 95.48
106 t CO2 in miscible reservoirs while the crude oil increased 50.78
106 t and sequestrated 127.88
106 t CO2 in immiscible reservoirs. The sequestration coefficient of CO2 miscible reservoirs was larger than immiscible reservoirs. That is mainly because that when CO2 reaches miscible state with crude oil, it can displace more oil and further spare more space for CO2 accumulation.

Table 7 Prediction results of Fang 5 block. Methods

Recovery factor after water flooding

Recovery factor after CO2 flooding

Recovery increment

Sequestration coefficient

Numerical simulation Stream tube simulation

22.3 22.8

34.0 35.4

11.7 12.6

0.256 0.235

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Table 8 Ranking of low permeability reservoirs CO2 flooding appraisal value in Yanchang Oilfield. Oil field

Block

Horizon

Geological reserves value

Value

DB WQ … CK NNW WYB GGY … GGY NNW

FX WWZ … BB XY YMH T114 … DBLQ SSL

Chang Chang … Chang Chang Chang Chang … Chang Chang

207 2200 … 1864 875 213 1008.98 … 4502.8 1225

0.858 0.832 … 0.533 0.530 0.528 0.526 … 0.457 0.447

6 4þ5 8 6 8 6 6 4þ5

Table 9 Potential estimation of low permeability reservoirs of CO2 flooding in Yanchang Oilfield. Oil field

Total number of reservoir in block

Suitable for CO2 flooding reservoir

Suitable for CO2 flooding reservoir number proportion

Geological reserves value (104 t)

Suitable for CO2 flooding reserves (104 t)

Suitable for CO2 flooding reservoir reserves proportion

XZC JB YN XB DB WQ CK QLC GGY WJC QPC QHZ PL NNW NQ XSW YW ZL HS ZC WYB ZB Total

13 15 5 3 20 34 8 8 6 1 1 3 4 10 4 8 2 4 4 5 16 4 178

12 14 4 3 20 34 8 1 1 0 1 2 4 5 4 8 2 4 4 5 11 3 150

0.92 0.9333 0.8 1.00 1.00 1.00 1.00 0.13 0.17 0.00 1.00 0.67 1.00 0.50 1.00 1.00 1.00 1.00 1.00 1.00 0.6875 0.75 0.84

10,685 12,340.5 25,315.5 12,011.9 14,431.6 37,080 7004.23 12,691 9624.31 8111 4305.2 9894.63 1987 7595 1139.2 11,601 647.84 4080 2068.16 7619.05 13,923.9 4981.9 219,138

10,495 12,071 24,727.33 12,011.87 14,431.64 37,080 7004.23 1934 1670.31 0 4305.2 4321.63 1987 2065 1139.2 11,601 647.84 4080 2068.16 7619.05 11,141.7 3872.9 176,274.1

0.98 0.97816 0.97677 1.00 1.00 1.00 1.00 0.15 0.17 0.00 1.00 0.44 1.00 0.27 1.00 1.00 1.00 1.00 1.00 1.00 0.80019 0.78 0.80

4. Conclusions Based on the characteristics of Yanchang Oilfield, this paper presented a reservoir screening standard that was suitable for CO2-EOR and geological sequestration in Yanchang Oilfield in China for the first time. CO2 sequestration coefficient RSCO2 was introduced to better reflect the variation tendency of CO2 storage capacity, and stream tube simulation method was proposed to figure out CO2 sequestration coefficient and oil recovery more precisely and efficiently. This method is more convenient than numerical simulation method, and the data for this method is easier to obtain. In addition, this appraisal method can also be used for other analogous potential evaluation in other oilfields.

Table 10 The results of assessment of miscible flooding of Yanchang Oilfield. Oil field

Geological reserves value (104 t)

Recovery by water flooding (%)

Recovery by CO2 flooding (%)

Recovery increment (%)

Sequestration coefficient (t/t)

Oil production Increment (104 t)

Sequestration potentials (104 t)

XZC JB XB WQ QLC QHZ PL XSW YW ZC ZB

10,495 12,071 12,011.87 37,080 1934 4321.63 1987 11,601 647.84 7619.05 3872.9

20.45 23.71 21.36 22.06 24.91 25.6 22.97 21.51 19.74 23.65 23.02

34.42 36.67 30.49 35.15 38.1 39.66 36.72 33.9 30.43 33.92 36.87

13.97 12.96 9.13 13.09 13.19 14.06 13.75 12.39 10.69 10.27 13.85

0.36 0.24 0.24 0.25 0.25 0.3 0.27 0.26 0.26 0.24 0.29

1466.152 1564.402 1096.684 4853.772 255.0946 607.6212 273.2125 1437.364 69.2541 782.4764 536.3967

40.71 114.75 93.58 399.87 367.53 2226.45 288.85 2204.48 704.86 3043.97 63.78

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Table 11 The results of assessment of immiscible flooding of Yanchang Oilfield. Oil field

Geological reserves value (104 t)

Recovery by water flooding (%)

Recovery by CO2 flooding (%)

Recovery increment (%)

Sequestration coefficient (t/t)

Oil production increment (104 t)

Sequestration potentials (104 t)

YN DB CK GGY WJC QPC NNW NQ ZL HS WYB

24,727.33 14,431.64 7004.23 1670.31 0 4305.2 2065 1139.2 4080 2068.16 11,141.7

21.36 20.69 20.51 21 21 20.65 20.1 19.73 20.02 21.89 21.21

27.61 30.81 27.52 27.76 29.05 29.8 27.31 23.55 28.72 25.97 25.19

6.25 10.12 7.01 6.76 8.05 9.15 7.21 3.82 8.7 4.08 3.98

0.18 0.24 0.18 0.18 0.21 0.22 0.2 0.12 0.19 0.18 0.06

1545.45 1460.48 490.99 112.91 0 393.92 148.88 43.51 354.96 84.38 443.43

4450.91 3463.59 1260.76 300.65 0 947.14 413 136.70 775.2 372.26 668.50

148 blocks in Yanchang Oilfield were suitable for CO2-EOR and sequestration. CO2 flooding after water flooding can produce 180.21
106 t more crude oil and sequestrate 223.38
106 t CO2. The average incremental oil recovery rate of miscible flooding was 12.49% and the average CO2 sequestration coefficient was 0.27 t/t while the two values were 6.83% and 0.18 t/t for immiscible flooding. Acknowledgments This work was supported by the National Basic Research Program of China (973 program, grant no. 2011CB707302), and Chinese National Major Science and Technology Projects (2011ZX05016-006 and 2011ZX05009-004-001).We are grateful to all staff involved in this project, and also thank the journal associate editor and the reviewers. References [1] S. Bachu, J. Shaw, Evaluation of the CO2 sequestration capacity in Alberta's oil and gas reservoirs at depletion and the effect of underlying aquifers, J. Can. Pet. Technol. 42 (9) (2003) 51e61. [2] S. Bachu, D. Bonijoly, J. Bradshaw, R. Burruss, S. Holloway, N.P. Christensen, O.M. Mathiassen, CO2 storage capacity estimation: methodology and gaps, Int. J. Greenhouse Gas Control 1 (4) (2007) 430e443. [3] J. Bradshaw, S. Bachu, D. Bonijoly, R. Burruss, S. Holloway, N.P. Christensen, O.M. Mathiassen, CO2 storage capacity estimation: issues and development of standards, Int. J. Greenhouse Gas Control 1 (1) (2007) 62e68. [4] J.J. Taber, F.D. Martin, R.S. Seright, EOR screening criteria revisited-part 1: introduction to screening criteria and enhanced recovery field projects, SPE Reservoir Eng. 12 (3) (1997) 189e198. [5] D. Diaz, Z. Bassiouni, W. Kimbrell, J. Wolcott, Screening criteria for application of carbon dioxide miscible displacement in waterflooded reservoirs containing light oil, in: SPE/DOE Improved Oil Recovery Symposium, 1996. [6] J. Shaw, S. Bachu, Screening, evaluation, and ranking of oil reservoirs suitable for CO2-flood EOR and carbon dioxide sequestration, J. Can. Pet. Technol. 41 (9) (2002). [7] F. Gozalpour, S.R. Ren, B. Tohidi, CO2 EOR and storage in oil reservoir, Oil Gas Sci. Technol. 60 (3) (2005) 537e546. [8] T. Babadagli, Optimization of CO2 Injection for Sequestration/Enhanced Oil Recovery and Current Status in Canada, 2006, pp. 261e270. [9] G. Moritis, CO2 sequestration adds new dimension to oil, gas production, Oil Gas J. 101 (9) (2003) 39e44. [10] Z. Yunchuan, X. Yu, H. Tianjiang, Screening method based on fuzzy optimum for gas injection in candidate reservoir, J. Southwest Pet. Inst. ISSN: 1000-2634 27 (1) (2005) 44e47 (in Chinese). [11] L. Huaiyan, G. Chenglin, G. Baocong, New screening method for reservoir by CO2 injection miscible flooding, J. China Univ. Pet. 32 (1) (2008) 72e76 (in Chinese). [12] Z. Shunpeng, Y. Xiuwen, Fuzzy hierarchy analysis-based selection of oil reservoirs for gas storage and gas injection, Henan Pet. 19 (4) (2009) 40e46 (in Chinese). [13] S. Pingping, L. Xinwei, L. Qiujie, Methodology for estimation of CO2 storage capacity in reservoirs, Pet. Explor. Dev. 36 (2) (2009) 216e220. [14] S. Bachu, Comparison Between Methodologies Recommended for Estimation of CO2 Storage Capacity in Geological Media, Report by the CSLF Task Force on CO2 Storage Capacity Estimation and the US DOE Capacity and Fairways Subgroup of the Regional Carbon Sequestration Partnerships Program-Phase III Report, 2008. [15] S. Bachu, D. Bonijoly, J. Bradshaw, R. Burruss, N.P. Christensen, S. Holloway, O.M. Mathiassen, Estimation of CO2 storage capacity in geological media, phase 2, in: Prepared for the Task Force on CO2 Storage Capacity Estimation for the Technical Group of the Carbon Sequestration Leadership Forum, 2007. [16] S. Wang, H. Jiang, Determine level of thief zone using fuzzy ISODATA clustering method, Transp. Porous Media 86 (2) (2011) 483e490. [17] W. Peixi, Z. Jing, Application and design of fuzzy intelligent evaluation software for sand production and steam channeling prediction of steam injection well, Procedia Eng. 24 (2011) 546e550.