International Journal of GeophysicsVolume 2012 (2012), Article ID 648781, 11 pagesdoi:10.1155/2012/648781

Review Article

Frequency-Dependent Streaming Potentials: A Review

L. Jouniaux¹ and C. Bordes²

¹Institut de Physique du Globe de Strasbourg, UdS-CNRS UMR 7516, Université de Strasbourg, 5 rue René Descartes, 67084 Strasbourg, France²Laboratoire des Fuides Complexes et leurs Réservoirs, UPPA-CNRS UMR5150, Université de Pau et des Pays de l'Adour, 64013 Pau, France

Received 1 July 2011; Accepted 14 November 2011

Academic Editor: Tsuneo Ishido

Copyright © 2012 L. Jouniaux and C. Bordes. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

The interpretation of seismoelectric observations involves the dynamic electrokinetic coupling, which is related to the streaming potential coefficient. We describe the different models of the frequency-dependent streaming potential, mainly Packard's and Pride's model. We compare the transition frequency separating low-frequency viscous flow and high-frequency inertial flow, for dynamic permeability and dynamic streaming potential. We show that the transition frequency, on a various collection of samples for which both formation factor and permeability are measured, is predicted to depend on the permeability as inversely proportional to the permeability. We review the experimental setups built to be able to perform dynamic measurements. And we present some measurements and calculations of the dynamic streaming potential.

1. Introduction

Electrokinetics arise from the interaction between the rock matrix and the pore water. Therefore electrokinetic phenomena are often observed in aquifers, volcanoes, and hydrocarbon or hydrothermal reservoirs. Observations show that seismoelectromagnetic signals associated to earthquakes can be induced by electromagnetic induction [1, 2] or by electrokinetic effect [3, 4]. The electrokinetic phenomena are due to pore pressure gradients leading to fluid flow in the porous media or fractures and inducing electrical fields. These electrokinetic effects are associated to the electrical double layer which was originally described by Stern. The electrokinetic signals can be induced by global displacements of the reservoir fluids (streaming potential) or by the propagation of seismic waves (seismoelectromagnetic effect). As soon as these pressure gradients have a transient signature, the dynamic part of the electrokinetic coupling has to be taken into account by introducing the dependence on fluid transport properties.

It is generally admitted that two kinds of seismoelectromagnetic effects can be observed. The dominant contribution, commonly called “coseismic”, is generated close to the receivers during the passage of seismic waves. The second kind, so-called “interfacial conversion” [5], is very similar to dipole radiation and is generated at physicochemical interfaces due to strong electrokinetic coupling discontinuities. This interface conversion is often perceived to have the potential to detect fine fluids transitions with higher resolution than seismic investigations, but in practice, signals are often masked by electromagnetic disturbances, especially when generated at great depth.

Nevertheless recent field studies have focused on the seismoelectric conversions linked to electrokinetics in order to investigate oil and gas reservoirs [6] or hydraulic reservoirs [5, 7–13]. It has been shown using these investigations that not only the depth of the reservoir can be deduced, but also the geometry of the reservoir can be imaged using the amplitudes of the electroseismic signals [14]. Moreover fractured zones can be detected and permeability can be measured using seismoelectrics in borehole [15–18]. This method is especially appealing to hydrogeophysics for the detection of subsurface interfaces induced by contrasts in permeability, in porosity, or in electrical properties (salinity and water content) [19–21].

The analytical interpretation of the seismoelectromagnetic phenomenon has been described by Pride [22], by connecting the theory of Biot [23] for the seismic wave propagation in a two-phase medium with Maxwell’s equations, using dynamic electrokinetic couplings. The seismoelectromagnetic conversions have been modeled in homogeneous or layered saturated media [12, 21, 24–26] with applications to reservoir geophysics [27].

Theoretical developments showed that the electrical field induced by the -waves propagation is related to the acceleration [12]. The electrokinetic coupling is created at the interface between grains and water, when there is a relative motion of electrolyte ions with respect to the mineral surface. Thus, seismic wave propagation in fluid-filled porous media generates conversions from seismic to electromagnetic energy which can be observed at the macroscopic scale, due to this electrokinetic coupling at the pore scale. The seismoelectric coupling is directly dependent on the fluid conductivity, the fluid density, and the electric double layer (the electrical interface between the grains and the water) (see [28], in this special issue “Electrokinetics in Earth Sciences” for more details). For more details on the surface complexation reactions see Davis et al. [29] or Guichet et al. [30]. It can be accurately quantified in the broad band by a dynamic coupling [22] which can be linked in the low-frequency limit to the steady-state streaming potential coefficient largely studied in porous media [30–44].

Laboratory experiments have also been investigated for a better understanding of the seismoelectric conversions [45–56]. These papers describe the laboratory studies performed to investigate this dynamic coupling. An oscillating pore pressure must be applied to a rock sample, and because of the relative motion between the rock and the fluid, an induced streaming potential can be measured. Depending on the oscillating frequency of the fluid, the fluid makes a transition from viscous dominated flow to inertial dominated flow. As the frequency increases, the motion of the fluid within the rock is delayed and larger pressure is needed. In order to know the dynamic coupling, both real and imaginary parts of the streaming potential must be measured.

2. From Dynamic Streaming Potential to Seismoelectromagnetic Coupling

The steady-state streaming potential coefficient is defined as the ratio of the streaming potential to the driving pore pressure: which is called the Helmholtz-Smoluchowski equation, where , , and are the fluid conductivity, the dielectric constant of the fluid, and the fluid dynamic viscosity respectively (see [28]). In this formula the surface electrical conductivity is neglected compared to the fluid electrical conductivity. The potential is the electrical potential within the double layer on the slipping plane. Although the zeta potential can hardly be modeled for a rock and although it cannot be directly measured within a rock, the steady-state streaming potential coefficient can be measured in laboratory, by applying a fluid pressure difference () and by measuring the induced streaming electric potential () [30, 38, 39, 44, 57]. The electrical potential itself depends on fluid composition and and the water conductivity [29–31, 38, 40, 42, 44, 58].

2.1. Packard’s Model

Packard [59] proposed a model for the frequency-dependent streaming potential coefficient for capillary tubes, assuming that the Debye length is negligible compared to the capillary radius, based on the Navier-Stokes equation: where is the angular frequency, is the capillary radius, and are the Bessel functions of the first order and the zeroth order, respectively, and is the fluid density.

The transition angular frequency for a capillary is More recently Reppert et al. [60] used the low- and high-frequency approximations of the Bessel functions to propose the following formula, which corresponds to their equation 26 corrected with the right exponents −2 and : with the transition angular frequency and showed that this model was not very different from the model proposed by Packard [59].

The complete development relating Biot’s theory and Maxwell’s equations has been published by Pride in 1994 [22].

2.2. Pride’s Model

Pride [22] derived the equations governing the coupling between seismic and electromagnetic wave propagation in a fluid-saturated porous medium from first principles for porous media. The following transport equations express the coupling between the mechanical and electromagnetic wavefields ([22] (174), (176), and (177)):

In the first equation, the macroscopic electrical current density is the sum of the average conduction and streaming current densities. The filtration velocity of the second equation is separated into electrically and mechanically induced contributions. The electrical fields and mechanical forces that create the current density and filtration velocity are, respectively, and , where is the pore-fluid pressure, is the solid displacement, and is the electric field. The complex and frequency-dependent electrokinetic coupling , which describes the coupling between the seismic and electromagnetic fields [22, 60], is the most important parameter in these equations. The other two coefficients, and , are the electric conductivity and dynamic permeability of the porous material, respectively.

The seismoelectric coupling that describes the coupling between the seismic and electromagnetic fields is complex and frequency-dependent Pride [22]: where is the low-frequency electrokinetic coupling, is related to the Debye-length, is a porous-material geometry term [65], and is a dimensionless number (detailed in Pride [22]).

The transition angular frequency separating low-frequency viscous flow and high-frequency inertial flow is defined as where is the porosity, is the intrinsic permeability, and is the tortuosity.

2.3. Further Considerations

The low-frequency electrokinetic coupling is related to the steady-state streaming potential coefficient by where is the rock conductivity. The electrokinetic coupling can be estimated by considering that steady-state models of can be applied to the calculation of . When writting with surface conductivity neglected, the steady-state electrokinetic coupling can be written as We can see that the steady-state electrokinetic coupling is inversely proportional to the formation factor.

The transition angular frequency separating viscous and inertial flows in porous medium can be rewritten by inserting with , as follows: where is the formation factor that can be deduced from resistivity measurements using Archie’s law.

Since the permeability and the formation factor are not independent but can be related by [66] with being a geometrical constant usually in the range 0.3–0.5 and being the hydraulic radius, the transition angular frequency can be written as Equation (12) shows that the transition angular frequency in porous medium is inversely proportional to the square of the hydraulic radius.

Recently Walker and Glover [74] proposed a simplified equation of Pride’s development assuming that the Debye length is negligible compared to the characteristic pore size, and assuming the following parameter: leading to with being the effective pore radius, and a transition angular frequency being

Garambois and Dietrich [12] studied the low-frequency assumption valid at seismic frequencies, meaning at frequencies lower than Biot’s frequency separating viscous and inertial flows and gave the coseismic transfer function for low-frequency longitudinal plane waves. In this case, and assuming Biot’s moduli , they showed that the seismoelectric field is proportional to the grain acceleration:

Equations (16), (9), and (1) show that transient seismo-electric magnitudes will be affected by the bulk density of the fluid, and the streaming potential coefficient which is inversely proportional to the water conductivity and proportional to the zeta potential (which depends on the water ).

2.4. The Electrokinetic Transition Frequency Compared to Hydraulic’s One

The theory of dynamic permeability in porous media has been studied by many authors [61, 65, 75–77].

The frequency behavior of the permeability is given by Pride (1994) [22]

The transition angular frequency for a porous medium is the same as (8). Charlaix et al. [62] measured the behavior of permeability with frequency on capillary tube, glass beads, and crushed glass. The dynamic permeability is constant up to the transition frequency above which it decreases, and the more permeable the sample is, the lower the transition frequency is. Other measurements have been performed on glass beads and sand grains [61]. The transition frequency () varies from 4.8 Hz to 149 Hz for samples having permeability in the range  to  m² (see Table 1), which are extremely high permeabilities.

Table 1: Measured or predicted transition frequency for dynamic streaming potential and permeability, for samples of porosity , formation factor , permeability , and half of the mean particle size , from (SED) Smeulders et al. [61], (CKS) Charlaix et al. [62], (SG) Sears and Groves [63], (P) Packard [59], (TGR) Tardif et al. [64], and (RMLJ) Reppert et al. [60]. *indicates predicted transition frequency from (3) and **Indicates the transition frequency computed by the authors.

Sample
Particle size
[%]

[m²]
[Hz]
Source

Capillary
254 (radius)

10–2.5* Hz
CKS

Capillary
508 (radius)

1.3–0.62* Hz
SG

Capillary G4
720 (radius)

0.31*–0.28** Hz
P

Capillary G2
826 (radius)

0.23*–0.21** Hz
P

Capillary 1
800–1100 (radius)

7.1 Hz
RMLJ

Glass beads
1.25–1.75
32
7.8

4.8 Hz
SED

Glass beads
850 (r)
50
2.8

6.2 Hz
CKS

Glass beads
580–700
31
8.7

20 Hz
SED

Glass beads
450 (r)
50
3.2

25 Hz
CKS

Glass beads
250 (r)
50
3

108 Hz
CKS

Glass beads
200–270
31
9

126 Hz
SED

Crushed glass
440 (r)
50
3

44 Hz
CKS

Crushed glass
265 (r)
50
3.2

45–103 Hz
CKS

Porous filter A
72.5–87

269 Hz
RMLJ

Porous filter B
35–50

710 Hz
RMLJ

Sand grains
1000–2000
31
9

6.7 Hz
SED

Sand grains
150–300
29
10.7

149 Hz
SED

Ottawa sand
200–250 (r)
31
4.7

230–273 Hz
TGR

The transition frequency indicates the beginning of the transition for both the permeability and the electrokinetic coupling. However the transition behavior and the cuttoff frequency are different between permeability and electrokinetic coupling ((7) and (17)), both depending on the pore-space geometry term but in different manner.

We calculated the predicted transition frequency with from (11) with  Pa.s and  kg/m³. The other parameters and are measured from different authors cited in Bernabé[78] (see Table 2). We also calculated the parameters for four Fontainebleau sandstone samples. It has been shown for these samples that (from Ruffet et al. [79]) and that with different values for according to the porosity. The following laws were chosen: for and for ranging between 8 and [80]. We can see that the transition frequencies are of the order of kHz and MHz and no more from 0.2 to 150 Hz as measured or calculated on glass beads, sand grains, crushed glass, or capillaries. We plotted the results of the transition frequency as a function of the permeability on these various samples in Figure 1. Although the formation factor is not constant with the permeability, it is clear that the transition frequency is inversely proportional to the permeability as and varies from about 100 MHz for  m² to about 10 Hz for  m², so by seven orders of magnitude for nine orders of magnitude in permeability.

Table 2: Predicted transition frequency (from (11)), for dynamic streaming potential, for samples of porosity , formation factor , and permeability , from (1) calculated in the present study, and measured by (2) Taherian et al. [67], (3) Morgan et al. [68], (4) Fatt [69], (5) Wyble [70], (6) Dobrynin [71], (7) Chierici et al. [72], and (8) Yale [73].

Sample
[%]

[m²]
[Hz]

Fontainebleau sandstone¹
20
25

3.2 kHz

Fontainebleau sandstone¹
15
45

4.4 kHz

Fontainebleau sandstone¹
10
102

6.2 kHz

Sandstone-S22²
31.2
6

9.7 kHz

Sandstone-S47²
20
14.4

13 kHz

Boise⁸
26
12

14.7 kHz

Berea sandstone500⁸
20
20

16.2 kHz

Sandstone-S42²
19.7
14.7

16.2 kHz

Sandstone-S45²
21
11.7

18.8 kHz

Fahler 162⁸
3
294

20 kHz

Sandstone-S43²
21.2
13

23.5 kHz

Pliocene 41⁷
21
144.9

26.1 kHz

Pliocene 35⁷
20
156.2

27.5 kHz

Berea sandstoneC2H³
19.8
15.1

27.7 kHz

Sandstone-S50²
18.3
17.2

30 kHz

Triassic38⁷
21
12.6

31.4 kHz

Triassic34⁷
20
13.9

32.7 kHz

Berea sandstoneB2³
20.3
15.2

39.7 kHz

Sandstone-S5²
26.4
8.7

45 kHz

Sandstone-S35²
18.75
17.4

46.5 kHz

Massillon DH⁸
16
23.8

51.4 kHz

Cambrian 16⁷
14
312.5

53.6 kHz

Fontainebleau sandstone¹
5
412

59.4 kHz

Berea sandstoneD1³
18.5
18.4

66.5 kHz

Tensleep1⁴
15
18.9

70.3 kHz

Tertiary 807⁸
22
14.9

71.1 kHz

Cambrian 6⁷
8.1
90.9

76.1 kHz

Torpedo⁶
20
41.7

84.9 kHz

Miocene 7⁷
8.3
384.6

94 kHz

Cambrian 14⁷
11
52.6

94.5 kHz

Sandstone Triassic27⁷
18
20

110.5 kHz

Sandstone-S9²
20.9
12

126.2 kHz

Triassic26⁷
18
17.2

135.7 kHz

Sandstone-S6²
22.8
10.6

180.7 kHz

Berea 100H⁸
17
17.2

188.4 kHz

Sandstone S15²
21.8
13.9

256.7 kHz

Kirkwood⁵
15
40

331.6 kHz

Indiana DV⁸
27
12

440.3 kHz

Island Rust A1³
14.6
52.5

579 kHz

Bradford⁵
11
90

700.3 kHz

Austin chalk³
23.6
22.7

763 kHz

Massillon DV⁸
19
27.8

830.4 kHz

Sandstone-S34²
21.35
13.7

1.06 MHz

Sandstone S44²
15.7
24.5

1.5 MHz

Indiana L. SA1³
18
29.2

2.9 MHz

Tennessee A1³
5.5
180.3

3.8 MHz

AZPink (Coconino)³
10.3
62.4

4.04 MHz

Leuders L.SA1³
15.2
41.5

5.3 MHz

Sandstone-S40²
10.9
130

6.4 MHz

Sandstone-S23²
18.8
40.7

8.1 MHz

Fahler 189⁸
1.9
714.3

11.1 MHz

Penn blue A1³
3.9
219

11.7 MHz

AZChoclate2³
9.5
159.3

17.2 MHz

Fahler 161⁸
2.3
416.7

38.2 MHz

Fahler 142⁸
7.6
164

48.5 MHz

Sandstone S21²
12.1
65

81.7 MHz

Fahler 154⁸
4.6
263.1

86.4 MHz

Fahler 192⁸
4.4
128.2

137.9 MHz

(a)

(b)

Figure 1: The transition frequency (in ) predicted in the present study with from (11) with Pa.s and kg/m³ as a function of the permeability (in m²). The transition frequency varies as . The parameters of the samples, and , are measured from different authors on various samples cited in Tables 1 and 2.

3. Experimental Apparatus and Procedure

Several experimental setups were proposed to provide the sinusoidal pressure variations.

The first experimental apparatus proposed a sinusoidal motion delivered by a sylphon bellows which was driven by a geophone-type push-pull driver (Figure 2 from Packard [59]). The low-frequency oscillator (0.01 Hz to 1 kHz) was used for operation of the push-pull geophone driver. Similar setups were proposed by Thurston [81] (Figure 3) and Cooke [82], so that frequency of this kind of source was 1–400 Hz [82], 20–200 Hz [59], and 10–700 Hz [81]. The induced pressure was up to 2 kPa. More recently Schoemaker et al. [83] used a so-called Dynamic Darcy Cell (DCC) with a mechanical shaker connected to a rubber membrane leading to a frequency range for the oscillating pressure 5 to 200 Hz. The sinusoidal fluid flow was also applied by a displacement piston pump directly connected to the electrodes chambers (Figure 4 from [63, 88]). The piston was mounted on a Scotch Yoke drive attached to a controllable speed AC motor [84]. The frequency range of this source was then 0.4 Hz to 21 Hz and the pressure up to 15 kPa. Pengra et al. [85] used a piston rod attached to a loudspeaker driven by an audio power amplifier (Figure 5). They performed measurements up to 100 Hz, with an applied pressure of 5 kPa RMS. More recently it was proposed by Reppert et al. [60] to use an electromechanical transducer (Figure 6), and these authors covered a frequency range 1–500 Hz. The vibrating exciter proposed by Schoemaker et al. [86] was used from 5 Hz to 200 Hz. Recently Tardif et al. [64] used an electromagnetic shaker operating in the range 1 Hz to 1 kHz and provided measurements up to 200 Hz. Higher frequencies have been investigated [49, 50, 52, 54, 55] for the detection of the interfacial conversions.

Figure 2: The sylphon bellows is driven by a geophone-type push-pull driver to apply a sinusoidal motion to the sample (modified from [59]).

Figure 3: Experimental setup used by Thurston [87] (modified from [87]).

Figure 4: Experimental setup used by Groves and Sears (modified from [88]).

Figure 5: Experimental setup used by Pengra et al. [85] for streaming potential and electro-osmosis measurements (modified from [85]).

Figure 6: Experimental setup used by Reppert et al. [60] (modified from [60]).

The electromagnetic noise radiating from such equipment must be suppressed by shielding the setup and wires (shielded twisted cable pairs) [64, 86]. Moreover it is essential to have a rigid framework. A mechanical resonance can occur in the cell/transducer system (at 70 Hz in [85]), and the noise associated with mechanical vibration can be suppressed puting an additional mass to the frame [64].

Once the oscillatory pressure is applied, the pressure must be measured. Most of the setups include piezoelectric transducers to measure the pressure difference over the capillary or the porous sample. Reppert et al. [60] proposed to use hydrophones that have a flat response from 1 to 20 kHz. Tardif et al. [64] proposed to use dynamic transducers with a low-frequency limit 0.08 Hz and a maximum frequency of 170 kHz.

The electrodes are usually Ag/AgCl or platinum electrodes. The electrodes used by Schoemaker et al. [86] were sintered plates of Monel (composed of nickel and copper). The electrical signal must be measured using preamplifiers or a high-input impedance acquisition system. Since the impedance of the sample depends on the frequency, one must correct the measurements from this varying-impedance to be able to have a correct streaming potential coefficient [60]. Moreover the electrodes at top and bottom of the sample can behave as a capacitor, requiring a correction using impedance measurements too [86].

The sample is usually saturated and it is emphasized that the sample should be left until equilibrium with water. This equilibrium can be obtained by leaving the sample in contact with water for some time, and by flowing the water within the sample several times by checking the and the water conductivity until an equilibrium is reached [39]. The procedure including water flow is better because the properties of the water can be measured. When the properties of the water are measured only before saturating the sample, the resulting water once in contact with the sample is not known. Usually the water is more conductive when in contact with the sample, and the can change. Recalling that the streaming potential is proportional to the zeta potential (which depends on ) and inversely proportional to the water conductivity (1), it is essential to know properly the and the water conductivity.

4. Measurements and Calculations of the Dynamic Electrokinetic Coefficient

The absolute magnitude of the streaming potential coefficient normalized by the steady-state value was calculated by Packard [59] as which is equal to (2), but expressed as a function of the parameter , the transition frequency being obtained for (Figure 7). The streaming potential coefficient is constant up to the transition angular frequency and then decreases with increasing frequency.

Figure 7: The absolute magnitude of the normalized streaming potential coefficient calculated by Packard [59] using (19) where , equivalent to (2) (modified from [59]).

Sears and Groves [63] measured the streaming potential coefficient on a capillary of radius 508 μm which was coated with clay-Adams Siliclad and then incubated with 1% bovine serum albumin and filled with 0.02 M Tris-HCl at 7.32. They reported the streaming potential and the pressure difference as a function of frequency in the range 0–20 Hz. We calculated the resulting streaming potential coefficient (see Figure 8) which decreases from about to  V/Pa. These authors computed the zeta potential and concluded that the zeta potential is independent of the frequency with an average value of 28.8 mV. Moreover they concluded that the zeta potential is also independent of the capillary radius and capillary length.

Figure 8: The streaming potential coefficient measured as a function of frequency by Sears and Groves [63] on a capillary coated with clay, incubated with BSA in 0.02 M Tris-HCl.

The value of the streaming potential coefficient on Ottawa sand measured at 5 Hz by Tardif et al. [64] was  V/Pa using a 0.001 mol/L NaCl solution to saturate the sample. Values between 1 and  V/Pa were measured on samples saturated by 0.1 M/L NaCl brine [85]. A compilation of numerous streaming potential coefficients measured on sands and sandstones at various salinities in DC domain [44] showed that , where is in V/Pa and in S/m. A zeta potential of −17 mV can be inferred from these collected data, assuming the other parameters (see (1)) independent of water conductivity. These assumptions are not exact, but the value of zeta is needed for numerous modellings which usually assume the other parameters independent of the fluid conductivity. Therefore an average value of −17 mV for such modellings can be rather exact, at least for medium with no clay nor calcite.

Reppert et al. [60] calculated the real part and the imaginary part of the theoretical Packard’s streaming potential coefficient (2) for different capillary radii (see Figure 9). It can be seen that the larger the radius is, the lower the transition frequency is, as shown previously by the different theories. Recent developments by the group of Glover have been performed to build a new setup and to make further measurements on porous samples: two papers detail these studies in this special issue on Electrokinetics in Earth Sciences.

Figure 9: The real and imaginary part of Packard's model (2) calculated by Reppert et al. [60] for three capillary radii: 100 μm (continuous line), 50 μm (dashed line), and 10 μm (point line) (modified from [60]).

5. Conclusion

Since the theory of Pride in 1994 [22], the dynamic behavior of the streaming potential is known for porous media. However few experimental results are available, because of the difficulty to perform correct measurements at high frequency. Up to now, measurements of the frequency-dependence of the streaming potential have been performed up to 200 Hz on high-permeable samples. The main difficulty arises from electrical noise induced by mechanical vibration. Moreover it has been emphasized that the measurements must be corrected by impedance measurements as a function of frequency too because the impedance of the sample depends on frequency. Further theoretical developments performed by Garambois and Dietrich [12] studied the low-frequency assumption valid at frequencies lower than the transition frequency. We show that this transition frequency, on a various collection of samples for which both formation factor and permeability are measured, is predicted to depend on the permeability as inversely proportional to the permeability.

Acknowledgments

This work was supported by the French National Scientific Center (CNRS), by the National Agency for Research (ANR) through TRANSEK, and by REALISE the “Alsace Region Research Network in Environmental Sciences in Engineering” and the Alsace Region. The authors thank two anonymous reviewers and the associate editor T. Ishido for very constructive remarks that improved this paper.

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