Results and Discussion of Polymer Flooding Simulation

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1
SIMULATION OF POLYMER FLOODING APPLIED FOR OIL FIELD IN
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PHITSANULOK BASIN
3
Jutikarn Kanarak* and Kriangkri Trisarn
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Running head: Simulation of Polymer Flooding in Phitsanulok Basin
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Abstract
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This paper examines two questions: (1) study and compare of oil recovery
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efficiency between the best case of waterflooding and polymer flooding by using
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reservoir simulation technique and, (2) apply the discount cash flow to optimize
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the polymer flooding selection from each scenario under current Dubai oil
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prices. Three sizes of oil fields are modeled in anticline reservoir structure with
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the original oil in place (OOIP) of 100, 30 and 5 million barrels respectively.
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Each oil field has many production methods by using different polymer
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concentrations and injection periods. The large size reservoir of model A100, oil
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recovery has increased from waterflooding of 3.86-7.24% OOIP. The polymer
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flooding has IRR range from 28.40-43.76% and PIR of 0.37-0.51, and the best
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case is the scenario that used polymer concentration of 1,000 ppm and injection
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period of 3rd-11thyear, that has net present value (NPV) of 170 MMUS$. The
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medium size reservoir of model A30, oil recovery has increased from
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waterflooding of 2.42-5.48% OOIP. The polymer flooding has IRR range from
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53.91-56.76% and PIR of 0.36-0.40, and the best case is the scenario that used
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polymer concentration of 1,000 ppm and injection period of 3rd-10thyear, that has
*
School of Geotechnology, Institute of Engineering, Suranaree University of
Technology, 111 University Avenue, Muang District, Nakhon Ratchasima 30000,
Thailand.
E-mail: [email protected]
*
Corresponding Author
2
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NPV of 53 MMUS$. The small size reservoir of model A05, oil recovery has
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increased from waterflooding of 4.39-4.62% OOIP. The polymer flooding has
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IRR range from 20.95-21.73% and PIR of 0.66-0.76, and the best case is the
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scenario that used polymer concentration of 600 ppm and injection period of 4th-
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20thyear, that has NPV of 15 MMUS$.
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Keywords: Recovery efficiency, Polymer flooding, Waterflooding, Reservoir
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simulation
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Introduction
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The oil field in Phitsanulok Basin, located in the central part of Thailand. This
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study focused on Sirikit oil field where it is a part of the Phitsanulok Basin. The
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Sirikit oil field has been produced by primary and secondary oil recoveries together
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with the production of 22978 bbl/d (Department of Mineral Fuels., 2009).
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secondary recovery, water injection has been applied to maintain reservoir pressure
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with some successes; it is still water breakthrough due to high mobility ratio and
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heterogeneity of geology that has actually occurred as high water cut stage. It causes
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poor performance of waterflooding. In order to improve the oil recovery, the polymer
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flooding is an attractive alternative to conventional waterflooding.
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modifications need to be made to a waterflooding to enable polymer injection and
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recovery of additional oil. Additional polymers with flood water can increase the
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viscosity of the displacing phase (aqueous phase). The increased viscosity of water
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during polymer flooding causes the change of water-oil fractional flow and the
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improvement in vertical and areal sweep efficiency. Thus more oil is recovered.
For
Minor
3
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Characteristics of Petroleum Reservoirs
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The Sirikit field is a main oil field in the Phitsanulok Basin that is the area of
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this study. The basin is an extensional Oligocene structure. The main reservoir
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intervals lie within the Oligocene-Miocene fluvio-lacustrine Lan Krabu Formation
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(Figure 1). The major reservoir facies are interpreted to be lacustrine mouth bars and
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fluvial distributary channels. The central area of the field is intensely faulted, whereas
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the western and eastern flanks are relatively undeformed. The field has an estimated
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STOIIP (stock tank oil initially in place) of some 800 MMbbl (million barrels). The
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main reservoirs contain undersaturated, light oil (39.4°API), and the initial reservoir
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pressure of 3500 psi at depth of 3850 m. The bubble point is lower 1800 psi (Trisarn,
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2006). Production started during 1982, and reservoir pressure quickly dropped to
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below bubble point, which resulted in higher producing gas/oil ratios (GOR) and
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lower oil rates. The reservoir drive energy was determined to be limited to solution
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gas expansion, which is aided by gas-cap expansion in some reservoirs. To preserve
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this energy and to optimize oil recovery, GOR limitations were set for the different
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reservoirs. As early as 1982, a water injection scheme was suggested for the Sirikit
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oil field. Consequently, in 1995 full-scale water injection commenced on the eastern,
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unfaulted flank of the field (Bruce et al., 1999). This study was the field development
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that investigated into optimizing recovery and identifying unswept oil volumes are
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considered.
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Enhanced Oil Recovery
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The increase oil recovery efficiency by polymer flooding is proven workable a
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widespread distribution, especially in the North America and China. In China, the
4
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study on enhanced oil recovery by chemical flooding has been carried out for more
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than 20 years (Han et al., 1999) and used both types of polymer which are
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Polyacrylamide (PAM) and Polysaccharide (Biopolymer or Xanthan Gum).
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results from China oil field can be proven that the polymer flooding technique can
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increase the oil recovery of the various reservoir types. This study used the Xanthan
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Gum for polymer flooding method, which has good performance more than the
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Polyacrylamide for high temperature in the reservoir.
The
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The objective of polymer flooding is to reduce mobility ratio based on
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increasing the water viscosity. In some cases, the polymer solution reduces the
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permeability of the reservoir rock to water. The mobility ratio between the displacing
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phase (polymer solution) and the displaced phase (oil) will be decreased, therefore,
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the oil water contact will move steady in the formation from injection well to
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production well.
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The polymer flooding into reservoir for control the mobility of injected phase
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can be shown in Figure 2. The figure show a schematic of a typical polymer flood
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injection sequence: a preflush is usually consisting of low salinity brine; an oil bank is
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injected by polymer; a fresh water buffer to protect the polymer solution from
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backside dilution; and the last are drive water.
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Reservoir Simulation Model design
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The performance prediction of water and polymer injection for the fields was
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built from the ECLIPSE OFFICE simulator model which confined well pattern.
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Three sizes of oil fields are modeled with the oil in place of 100, 30 and 5 million
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barrels respectively. Model sizes and dimensions are shown Table 1. Each oil field
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has many production methods that use different polymer concentrations and various
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times interval for injection. The properties of the reservoir are summarized in Table
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2. The simulation pertained to a confined well pattern, the symmetry element being
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represented by grid block of, 25 x 25 x 8 blocks (5000 cells) for all models, which are
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shown in Figure 3. Polymer flooding pattern design for a comprehensive of the
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flooding simulation which relies on the reservoir structure, drainage area, number of
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well, production and injection activity. The summary of water and polymer injection
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rate for each scenario is illustrated in Table 3.
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The structural of model A100 shows peripheral flood injection pattern. There
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are 17 production wells and 8 injection wells located in and around the reservoir
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boundary, respectively. The appropriate spacing of each well is approximately 1000
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ft. Model A30 shows peripheral flood injection pattern. There are 5 production wells
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and 4 injection wells located in and around the reservoir boundary, respectively. The
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appropriate spacing of each well is approximately 945 ft. Model A05 shows inverted
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three-spot flood injection pattern. There are a production well and 2 injection wells
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located at reservoir crest and down dip of the reservoir boundary, respectively. The
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appropriate spacing of each well is approximately 350 ft.
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The production and injection wells are located in the updip and downdip
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structure, respectively. The appropriate numbers of well are considered to optimum
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oil recovery, injection of polymer slug, polymer concentration and economic
114
evaluation.
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The structure model for the Sirikit oil field is very important for maximal
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improvement oil recovery. The field is geologically complex, being very faulted in a
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lacustrine environment and heterogeneity of the various reservoirs. Trisarn (2006) found
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vertical heterogeneity of porosity and permeability of the Sirikit L sand as shown in
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Figure 4.
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Results and Discussion of Polymer Flooding Simulation
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The base case from the waterflooding of each model was tested which need to
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found the best case as well as the highest oil recovery from the waterflooding. The
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results found, all models of the waterflooding that have highest oil recovery can be
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started within a reasonable time on 3rd year and water flood must be injected into the
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reservoir until the end of project life, for reservoir pressure support.
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The results of analysis obtained from the best scenario of the waterflooding
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(base case) and the application of the polymer flooding technique in the three reserved
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sizes of oil field with different polymer concentrations and various times interval for
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injection are shown in Table 4.
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There shows the scenarios of polymer injection that could have high
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performance oil recovery efficiency when compared to the best case of water
133
injection. All scenarios have more incremental of oil from the polymer injection than
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that would be gained from the water injection alone. For Model A100, oil recovery
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has increased 5.25, 4.60, 3.86, 6.37, 5.73, 4.98, 7.24, 6.58 and 5.83% of OOIP in
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scenario 2 to 10 respectively. Model A30, oil recovery has increased 4.25, 3.42, 2.42,
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4.96, 4.01, 2.87, 5.48, 4.33 and 3.13% of OOIP in scenario 2 to 10 respectively.
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Model A05, oil recovery has increased 4.40, 4.48, 4.39, 4.56, 4.39, 4.57, 4.52 and
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4.62% of OOIP in scenario 2 to 9 respectively.
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The results show that the polymer flooding can improve the water swept
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coefficient and the volumetric sweep efficiency, consequently, water cut in reservoir
7
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decreased. As a result, the polymer flooding method can successfully adjust the
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mobility ratio between polymer solution and oil phase in the reservoir that is
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effectively prompt of oil recovery efficiency, which are shown Figure 5-7.
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The effects of reducing the water cut and increasing the oil production rate are
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observed at all scenarios in each model. For example, model A100 with polymer
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concentration of 1,000 ppm and a time interval injection of 3rd-11th year, the oil
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production rate increases after injection of polymer solution on June 6th year, and at
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the end of polymer flooding on 11th year, the water cut of that reservoir decreases
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from 25.5% to 3.4% with a production rate increases from 2849 to 3667 bbl/day and
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the polymer flooding can maintains oil production rate more than receives from the
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waterflooding until June 21th year.
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Comparison between the waterflooding and polymer flooding from model
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A100, the oil saturation distribution after polymer flooding by injection polymer
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concentration of 1000 ppm with injection slug size of 0.12 pore volume (PV) has been
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selected to compare with the waterflooding (Figure 8-9). Before polymer flooding,
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the oil saturation in all layers has been still very high. From the waterflooding, the oil
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saturation has been decreased in small area around the wells only. After polymer
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flooding, in the most area where is oil in placed can be controlled by the injection
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wells and the production wells, the reservoir oil saturation has been decreased to the
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residual oil saturation, that is more oil has been produced.
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The comparison shows that oil saturation from polymer flooding has been
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apparently decreased, especially in the upper six layers. The polymer flooding has
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taken clearly effect on improving volumetric driving efficiency. On the other hand,
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the two lower layers have not effectiveness by polymer flooding because a reservoir
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with the aquifer may become difficult to be flooded, due to the flow of polymer
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solution in the reservoir could not be regulated and that is difficult respect to control
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of chemical loss.
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The increasing of polymer concentration can increase the oil recovery,
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however, the concentration of polymer need to be adjusted to the suitable injection
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rate to prevent the extreme adsorption mechanism on the rock surface and undesired
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blocking zones. If polymer slug size is very small, that is almost no enhanced oil
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recovery. Most of polymer has been adsorbed on the pore surface of the rock. In
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addition, the polymer injection with too high concentration more than appropriate
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concentration will make the larger particle size which plug in pore spaces. The oil
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recovery will be decrease due to the inaccessible pore volume that solid particle of
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polymer cannot flow through.
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The polymer injection within a reasonable time will make the highest oil
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recovery. The main important to improvement oil recovery is to maintain pressure in
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the reservoir for the stable pressure drop which control the oil optimum flow rate base
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on the Darcy’s Law. Therefore, the polymer injection in the early stage of a water
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flood is important as mention above and the simulation also provide the suitable time
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period to start polymer injection.
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The small reservoir geometry that has only a small oil bearing zone, such as
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model A05, the economic design of a flooding may be not possible. Due to it is very
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difficult to be flooded with respect to the control of chemical loss. Thus model A05
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need to be used to the lower polymer concentration injection with a long period of
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time, to prevent an adsorption and undesired blocking zone. The effect of polymer
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injection with incremental of oil recovery are shown in Figure 10.
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Economic Evaluation
Economic evaluation is the final step in this study on the application of
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polymer flooding for the enhanced oil recovery.
The objective of economic
193
evaluation is the commerciality of each model project as the result from the reservoir
194
simulation. Table 5 lists the economic evaluation parameters used in this study.
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From the result of polymer flooding in each model is compared to the best
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case of the waterflooding which is used the same water/polymer solution injection
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rate (displacing phase). The results of economic evaluation are shown in Table 6.
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This table contains for net present value (NPV), internal rate of return (IRR) and
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profit to investment ratio (PIR). For model A100, scenario of water injection has the
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IRR after tax and 8% discounted of 33.49% and PIR of 0.46, while scenarios of
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polymer injection have the IRR after tax and 8% discounted range from 28.40-43.76%
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and PIR of 0.37-0.51. Accordingly, the best operation case for model A100 is the
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scenario that used the polymer concentration of 1000 ppm and the time interval of
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injection 3rd-11th year, that has the best NPV of 170 MMUS$.
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Model A30, scenario of water injection has the IRR after tax and 8%
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discounted of 55.43% and PIR of 0.39, while scenarios of polymer injection have the
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IRR after tax and 8% discounted range from 53.91-56.76% and PIR of 0.36-0.40.
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Accordingly, the best case for model A30 is the scenario that used the polymer
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concentration of 1,000 ppm and the time interval of injection 3rd-10th year, that has the
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best NPV of 53 MMUS$.
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Model A05, scenario of water injection has the IRR after tax and 8%
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discounted of 21.72% and PIR of 0.83, while scenarios of polymer injection have the
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IRR after tax and 8% discounted range from 20.95-21.73% and PIR of 0.66-0.76.
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Accordingly, the best operation case for model A05 is the scenario used the polymer
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concentration of 600 ppm and the time interval of injection 4th-20th year, that has the
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best NPV of 15 MMUS$.
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Conclusions and Recommendations
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The heterogeneity of the geological conditions in the reservoirs causes the oil
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fields to have a high water cut stage, and low oil recovery efficiency using the
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waterflooding method.
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different size of oil fields with the various polymer concentrations by the reservoir
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simulation, the results found the polymer flooding can increase the oil recovery more
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than using the traditional waterflooding method only, due to the polymer solution can
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improve the water swept coefficient and the volumetric sweep efficiency. Finally,
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those have reduced the water cut in the oil reservoirs of heterogeneous geological
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condition.
The “Xanthan Gum” polymer solution is used in these oil fields
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simulation.
The reservoir with quite high temperature assures that this polymer
229
solution can increase the water viscosity.
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polymer solutions and oil will be decreased.
The application of the polymer flooding method in the
Therefore, the mobility ratio between
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Consequently, Model A100 with the 1000 ppm polymer solution injection and
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inject period of 3rd-11th year, there is an increased profit of 1370 barrel of oil
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production per ton of polymer injected, and the oil recovery efficiency will be
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increased 5.25% OOIP more than the waterflooding. For Model A30, with the 1000
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ppm polymer solution injection and injection period of 3rd-10th year, there is an
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increased profit of 1450 barrel of oil production per ton of polymer injected, and the
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oil recovery efficiency will be increased 4.25% OOIP more than the waterflooding.
11
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For Model A05, with the 600 ppm polymer solution injection and injection period of
239
4th-20th year, there is an increased profit of 820 barrel of oil production per ton of
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polymer injected, and the oil recovery efficiency will be increased 4.48% OOIP more
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than the waterflooding.
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The polymer flooding would not economic efficiency when the field used
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excess concentration of polymer, due to the big consumed amount of polymer. Thus
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the polymer flooding will make not profitable as well as the higher cost than the
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waterflooding.
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The heterogeneity effect of porosity and absolute permeability variation need
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to apply and test for individual productive reservoir to make a reliable result of the
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simulation result.
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The simulation models used in this study appear to be conceptual model not
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the real performance of oil field in the Phitsanulok Basin.
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Acknowledgement
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The authors wish to special thank to Asst. Prof. Thara Lekuthai who gave the valuable
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suggestion for this research. Also, we would like to acknowledge the School of
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Geotechnology, Suranaree University of Technology for all supports.
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256
References
257
Bruce, A.R., Sanlug, M., and Duivenvoorden, S. (1999). Correlation techniques,
258
perforation strategies, and recovery factors: an integrated 3-D reservoir
259
modeling study, Sirikit field, Thailand. AAPG Bulletin, 83(10): 1535-1551.
260
Department of Mineral Fuels, Ministry of Energy, Thailand. [DMF]. (2009). Annual
261
Report 2009 [On-line]. Available from: www.dmf.go.th. Accessed date: Aug 20,
12
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2010.
Gharbi, R.B.C. (2004). Use of reservoir simulation for optimizing recovery
performance. Journal of Petroleum Science and Engineering 42(2-4):183-194.
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Han, D.K., Yang, C.Z., Zhang, Z.Q., Lou, Z.H., and Chang, Y.I. (1999). Recent
266
development of enhanced oil recovery in china. Journal of Petroleum Science
267
and Engineering 22(1):181-188.
268
269
Lake, W.L. (1989). Enhanced Oil Recovery. New Jersey: Prentice-Hall, Eaglewood
Cliffs. 550 pp.
270
Li, X.P., Yu, L., Ji, Y.Q., Wu, B., Li, G.Z., Zheng, L.Q. (2009). New type flooding
271
systems in enhanced oil recovery. Chinese Chemical Letters 20(10): 1251-1254.
272
McCoy, S.T. and Rubin, E.S. (2008). The effect of high oil prices on EOR project
273
economics. Department of Engineering and Public Policy, Carnegie Mellon
274
University, Pittsburgh, USA. Available from: www.sciencedirect.com. Accessed
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date: Jan 15, 2010.
276
Morley, C.K., Lonnikoff, L., Pinyochon, N., and Seusutthiya, K. (2007). Degradation
277
of a footwall fault block with hanging-wall fault propagation in a continental-
278
lacustrine setting: How a new structural model impacted field development
279
plans, the Sirikit field, Thailand. AAPG Bulletin 91(11):1637-1661
280
Thang, P.D. (2005). Enhanced oil recovery in basement rock of the White Tiger Field
281
in offshore Southern Vietnam, [MEng. thesis]. School of Civil Engineering,
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Asian Institute of Technology. Pathumthani, Thailand, 133p.
283
Trisarn, K. (2006). Improvement oil recovery by water flooding in Thailand tertiary oil
284
field, [Research report]. School of Geotechnology, Institute of Engineering,
285
Suranaree University of Technology.
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Figure 1.
Schematic general stratigraphy of the Phitsanulok Basin and the
Sirikit field. The strata of interest are the Oligocene-Miocene
lacustrine deltaics of the Lan Krabu Formation (Bruce, et.al., 1999).
14
Figure 2. Schematic illustration of polymer flooding sequence,
(Lake, 1989).
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Figure 3. The model structure and confined well pattern of three reserve sizes.
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Figure 4. The reservoir sections show the vertical heterogeneities of reservoir.
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Figure 5. Production performance, Model A100-polymer 1,000 ppm-injected 3rd11th year.
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Figure 6. Production performance, Model A30-polymer 1,000 ppm-injected 3rd10th year.
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Figure 7. Production performance, Model A05-polymer 600 ppm-injected 4 th20th year.
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Figure 8. Oil saturation distribution after waterflooding@the end of project life,
Model A100-no polymer injection.
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Figure 9. Oil saturation distribution after polymer flooding@the end of project
life, Model A100-polymer 1,000 ppm-injection 3rd-11th year.
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Figure 10. Effect of polymer injection (barrel oil/ton of polymer).
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Table 1. Model sizes and dimensions
Model
Dimension (ft)
Area (acres)
Thickness (ft)
6,250 x 6,250
Horizontal grid
dimension (ft)
250
A100
896.75
100
A30
3,375 x 3,375
135
261.49
160
A05
1,250 x 1,250
50
35.87
56
24
Table 2. Summary of reservoir and fluid properties
Parameter
Properties
Depth
3,850 ft
Temperature
203°F
Rock type
Consolidated Sandstone
Porosity
19-26%
Oil gravity
39.4°API
Oil viscosity
2.1 cp
Permeability
9.2-586 md
Average kv/ kh
0.10
Datum depth
3,850 ft
Initial static reservoir pressure
3,500 psi
Oil formation volume factor
1.055-1.286 bbl/STB
Dissolved gas specific gravity
0.8
Bubble point pressure
1,800 psi
Water-oil contact depth
3,915 ft
25
Table 3. Injection rate of scenarios test
Model
A100
A30
A05
Injection
scenarios
Waterflooding
Preflush by water
Polymer injection
Driving water
Waterflooding
Preflush by water
Polymer injection
Driving water
Waterflooding
Preflush by water
Polymer injection
Driving water
Water injection
(BWPD/well)
1,000
500
200
Polymer/water
Injection (BWPD/well)
1,000
1,000
1,000
500
500
500
200
200
-
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Table 4. Basic data of polymer flooding
Model Pattern
A100
A30
Peripheral
flood
Peripheral
flood
Injector/ Distance Scenario
Producer between No.
injector
and
producer
(ft)
8/17
1,000
1
4/5
945
Polymer
concentration
(ppm)
Date of
water/
polymer
injection
Quantity
of injected
polymer
(ton x pv)
Incremental
oil
recovery
(%OOIP)
3rd-25th
-
-
2
Water inj.
(no-polymer)
1,000
3rd-11th
4,181x0.14
5.25
3
1,000
4th -12th
4,181x0.14
4.60
4
1,000
5th -13th
4,181x0.14
3.86
5
1,500
3rd-11th
6,272x0.14
6.37
6
1,500
4th
-12th
6,272x0.14
5.73
7
1,500
5th -13th
6,272x0.14
4.98
8
2,000
3rd-11th
8,365x0.14
7.24
9
2,000
4th -12th
8,365x0.14
6.58
10
2,000
5th -13th
8,365x0.14
5.83
1
Water inj.
(no- polymer)
1,000
3rd-25th
-
-
3rd-10th
929x0.12
4.25
3
1,000
4th
-11th
929x0.12
3.42
4
1,000
5th -12th
929x0.12
2.42
5
1,500
3rd-10th
1,394x0.12
4.96
6
1,500
4th -11th
1,394x0.12
4.01
7
1,500
5th -12th
1,394x0.12
2.87
8
2,000
3rd-10th
1,858x0.12
5.48
9
2,000
4th -11th
1,858x0.12
4.33
10
2,000
5th -12th
1,858x0.12
3.13
1
3rd-20th
-
-
2
Water inj.
(no-polymer)
600
3rd-20th
296x0.34
4.40
3
600
4th -20th
279x0.34
4.48
4
800
3rd-20th
395x0.34
4.39
5
800
4th -20th
372x0.34
4.56
6
1,000
3rd-20th
494x0.34
4.39
7
1,000
4th
-20th
465x0.34
4.57
8
1,200
3rd-20th
592x0.34
4.52
9
1,200
4th -20th
557x0.34
4.62
2
A05
Inverted
three-spot
2/1
350
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Table 5. Economic evaluation parameter
Project parameters
A100
A30
A05
Dubai oil price (US$/bbl)
80
80
80
Income tax (%)
50
50
50
Inflation rate (%)
2
2
2
Real discount rate (%)
8
8
8
0-2,000
5
5
5
2,000-5,000
6.25
6.25
6.25
5,000-10,000
10
10
10
10,000-20,000
12.5
12.5
12.5
>20,000
15
15
15
Concession (MMUS$)*
3.75
2.50
0.50
Geological and geophysical survey (MMUS$)
5
4
1
Production facility (MMUS$)
250
100
10
Drilling exploration & appraisal well (MMUS$)
10.5
6
1
Drilling and completion production well (MMUS$/well)
1.5
1.5
1.5
Facility cost of water injection well (US$/well)
60,000
60,000
60,000
Facility cost of polymer injection well (US$/well)
62,000
62,000
62,000
Maintenance cost of water injection well (US$/year)
80,000
60,000
40,000
Maintenance cost of polymer injection well (US$/year)
80,000
60,000
40,000
Abandonment cost (US$/well)
12,500
12,500
12,500
Operating cost of production well (US$/bbl)
30
25
20
Operating cost of water injection (US$/bbl)
0.5
0.5
0.5
Operating cost of polymer injection (US$/bbl)
1.0
1.0
1.0
Polymer purchasing price including transportation (US$/kg)
7
7
7
Sliding scale royalty (%)
Production level (bbl/day)
*MMUS$ = Million US Dollar
28
Table 6. Economic evaluation results summary
Model
Scenario
No.
A100
A30
A05
Amount
of
polymer
(ton)
Capital
cost
(MMUS$)
NPV
with8%
discounted
(MMUS$)
IRR
with8%
discounted
(%)
PIR
with8%
discounted
(Fraction)
1
Time of
water/
polymer
injection
(year)
23
-
307.33
141.94
33.49
0.46
2
9
4,181
337.10
170.31
43.76
0.51
3
9
4,181
337.10
150.83
33.28
0.45
4
9
4,181
337.10
135.62
28.84
0.40
5
9
6,272
351.74
169.31
43.38
0.48
6
9
6,272
351.73
150.25
33.08
0.43
7
9
6,272
351.73
134.90
28.62
0.38
8
9
8,365
366.38
167.37
43.00
0.46
9
9
8,365
366.37
149.21
32.81
0.41
10
9
8,365
366.37
133.86
28.40
0.37
1
23
-
126.54
49.60
55.43
0.39
2
8
929
133.04
53.05
54.33
0.40
3
8
929
133.04
50.83
55.31
0.38
4
8
929
133.04
52.53
56.76
0.39
5
8
1,394
136.29
52.99
54.91
0.39
6
8
1,394
136.29
50.51
55.21
0.37
7
8
1,394
136.29
52.22
56.72
0.38
8
8
1,858
139.55
52.24
53.91
0.37
9
8
1,858
139.55
49.75
55.08
0.36
10
8
1,858
139.55
51.75
56.68
0.37
1
18
-
17.15
14.26
21.72
0.83
2
18
296
19.34
14.49
21.21
0.75
3
17
279
19.22
14.69
21.73
0.76
4
18
395
20.03
14.38
21.12
0.72
5
17
372
19.87
14.61
21.67
0.74
6
18
494
20.72
14.27
21.03
0.69
7
17
465
20.52
14.51
21.61
0.71
8
18
592
21.42
14.18
20.95
0.66
9
17
557
21.17
14.42
21.54
0.68

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