**Research article**| 18 May 2022

# Advances in the hydraulic interpretation of water wells using flowmeter logs

Jesús Díaz-Curiel Bárbara Biosca Lucía Arévalo-Lomas María Jesús Miguel and Natalia Caparrini

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**Jesús Díaz-Curiel et al.**Jesús Díaz-Curiel Bárbara Biosca Lucía Arévalo-Lomas María Jesús Miguel and Natalia Caparrini

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^{1}Department of Energy and Fuels Systems, School of Mines and Energy, Universidad Politécnica de Madrid, Madrid, 28003, Spain^{2}Gobierno de España – Ministerio de Ciencia e Innovación, Madrid, 28046, Spain^{3}Department of Natural Resources and Environmental Engineering, School of Mining Engineering, Universidad de Vigo, Pontevedra, 36310, Spain

^{1}Department of Energy and Fuels Systems, School of Mines and Energy, Universidad Politécnica de Madrid, Madrid, 28003, Spain^{2}Gobierno de España – Ministerio de Ciencia e Innovación, Madrid, 28046, Spain^{3}Department of Natural Resources and Environmental Engineering, School of Mining Engineering, Universidad de Vigo, Pontevedra, 36310, Spain

**Correspondence**: Jesús Díaz-Curiel (j.diazcuriel@upm.es)

**Correspondence**: Jesús Díaz-Curiel (j.diazcuriel@upm.es)

Received: 17 Jul 2021 – Discussion started: 26 Aug 2021 – Revised: 18 Apr 2022 – Accepted: 21 Apr 2022 – Published: 18 May 2022

This paper reports on the methodology developed for a new hydraulic interpretation of flowmeter logs, allowing a better characterization of continental hydrological basins. In the course of a flowmeter log, different flow stretches are established, mostly corresponding to permeable layers (aquifers), among which there are other stretches mainly corresponding to less permeable layers (aquitards). In such hydrological basins of sufficient thickness, these flow stretches may not have the same hydraulic head. This fact brings about the need for a new hydraulic interpretation that provides the actual distribution of horizontal permeability throughout the aquifer at depth. The modified hydraulic interpretation developed in this study focuses on the differences of the effective pressure gradient (considered the difference between the hydraulic head in the well and the hydraulic head of each stretch) experienced by the different flow stretches along the well, due to the existence of different hydraulic heads. The methodology has been developed starting from a water well located in a multilayered aquifer within the so-called Madrid basin (the north-western part of the continental basin of the Tagus River), located in the centre of the Iberian Peninsula. In this well, a step-drawdown pumping test was conducted, in which the pumping rate versus drawdown and the specific capacity versus drawdown showed discrepancies with Darcian behaviour and an exponent of the Jacob equation of less than 1. Flowmeter logs were then recorded for different discharge rates and pump depths; the resulting water input from deeper permeable layers did not appear to show the expected relation with respect to drawdown. With the proposed methodology the results comply with the expected linearity and the cited discrepancies are solved.

One of the most interesting hydrogeological aspects of well pumping tests is that their results not only allow us to estimate the permeability and transmissivity obtained in the well, but that they can also be used to infer the behaviour of the aquifer when the lithological distribution of the basin in its location is known. This estimate of basin behaviour will be less accurate when knowledge of the lithology is local. In the case of step-drawdown pumping tests, this inference is generally known when the characteristic curves of the test show a conventional evolution, i.e. when the drawdown versus the extraction rate curve shows an increasing slope and the specific capacity decreases with drawdown. This is the case when, inside the well, in the near-wellbore zone or in the aquifer, head losses occur, whether linear or polynomial, whose effects are well recognized in step-drawdown pumping test curves (Helweg, 1994; Kawecki, 1995; Mathias and Todman, 2010).

These models provide an accurate representation of the aquifer behaviour for any pumping time. Among other results, Mathias and Todman (2010) found that the best fit was achieved by using a non-linear coefficient, called the “well loss coefficient”, which can be different for each step. The values of this coefficient were obtained using an analytical formula derived to relate this coefficient to the Forchheimer parameter. When the drawdown versus the extraction rate curve presents an increasing slope, as in the case of the step-drawdown test from Clark (1977) (a similar behaviour can be seen in the generic curves 2 and 3 shown in Fig. 1), there are different hydrogeological explanations. However, the slope decreases and the specific capacity versus the drawdown increases, i.e. when the hydric behaviour improves with increasing flow rate, as in the last two stages of the step-drawdown test from Van Tonder et al. (2001) (a similar behaviour can be seen in the generic curve 4 shown in Fig. 1). The only explanation known to date is that the well is not properly developed. In the following text, when such results occur, they are referred to as anomalous cases.

In step-drawdown pumping tests, there is no unified criterion for the duration that each step should have. Thus, in contrast to the values used for the characteristic curves of these tests in some studies (Shapiro et al., 1998; Karami and Younger, 2002), in this study, it is considered that the steps must be performed for sufficiently long periods to have reached quasi-steady states. These states have been reached when the temporal variation of the drawdown is less than 1 % of the total drawdown for each step. This criterion has been adopted by considering its equivalence with the criterion established by Zha et al. (2017) on the temporal derivative of drawdown for quasi-steady state conditions and by considering the validity of assimilating the drawdown in the well to the average behaviour of the different levels in a multilayer aquifer.

A situation that is not often considered in studies on great continental detrital basins that are hundreds of metres deep is that the diverse permeable layers crossed by water wells can have different hydraulic heads. If this difference exists, then the permeability value determined for each permeable layer is incorrect, leading to an error in the estimation of the flow rate provided by each layer and causing a very important deviation in aquifer modelling. Although this possibility has been cited in several publications (Molz et al., 1994; Crowder, 2002; Le Borgne, 2006), no methodology has been published to quantify its effects in water wells in large continental detrital basins.

Flowmeter logging is conventionally used to determine variations in the flow
velocity along a well casing, allowing water inputs at different depths that
contribute to the total discharge rate to be computed. These quantities are
used to estimate changes in hydraulic characteristics with depth, thereby
improving the management and rational exploitation of aquifers. In addition
to this conventional purpose, a process to provide information regarding
different hydraulic heads in fractured rock media from flowmeter logs was
proposed in several works by Paillet. Paillet (1998) showed the results of
two flowmeter logs obtained with a heat-pulse flowmeter (lower limit of
∼0.1 l min^{−1} and upper limit of ∼20.0 l min^{−1}) in
Waupun (Wisconsin, USA). These flowmeter logs were measured under ambient
and injection conditions at about 4 l min^{−1} and analysed for pumping or injection rates typically 1–5 l min^{−1}. We think that the relationship used to
estimate the transmissivity *T*_{k} of each fracture *k*, starting from the flow
into the borehole *q*_{k}, is ${q}_{k}^{b}-{q}_{k}^{a}=\mathrm{2}\mathit{\pi}{T}_{k}\left({w}^{a}-{w}^{b}\right)\cdot \mathrm{ln}\left({R}_{\mathrm{0}}/{r}_{\mathrm{w}}\right)$, where *a* and *b* address the ambient and stressed conditions, respectively, *w*^{a,b} are the water
levels in the borehole for these conditions, *R*_{0} is the distance to the “outer edges” of the fracture, and *r*_{W} is the borehole radius. This
relationship does not depend on the unknown value of the far-field head in
the aquifer *H*_{k}. Later, in Paillet (2000), $\sum {T}_{k}\cdot {H}_{k}={w}^{a}\cdot \sum {T}_{k}$ is used to determine *T*_{k}. In this work “the results of high capacity tests, where the effects of ambient hydraulic-head differences would not be significant” were discussed. The hydraulic head values (4.54, 4.91, 4.91, 4.91, and 4.91 m below ground level) obtained for the four productive intervals found in one of the analysed boreholes are also presented in that work, although the
process followed is not reflected in this paper. In Paillet (2000) the
hydraulic head estimates (centimetres above open hole water level) in the same borehole (+28, −11, −11, and −11 cm above open hole water level) are
shown. Based on this methodology, Day-Lewis et al. (2011) presented a
computer program for flow-log analysis of single holes applicable up to 10
levels, in which the hydraulic head of each zone is determined by minimizing
the differences between the flow rates obtained and those of the model and between the borehole's water level and far-field heads.

This communication presents the possibilities of the flowmeter log providing a hydrogeological explanation for the described anomalous cases. With this aim, in this work a method has been developed that uses flowmeter logs to provide information regarding different hydraulic heads in a multilayer basin. Determining these different hydraulic heads allows hydraulic reinterpretation that explains the abovementioned anomalous behaviours of the pumping test results.

To use flowmeter logs, a thorough pre-processing of results is necessary, without which the water inflow values determined in each filter can have very high errors and in turn allow an accurate determination of the head loss inside the well. Although different types of sensors have been used in well logging tools, spinner flowmeters are the most widely used in assessing the productivity of wells. Díaz-Curiel et al. (2020) proposed a complete reformulation for processing spinner flowmeter logs.

Another aspect related to the reliability of the flowmeter log results is the variability caused by differences in the near-wellbore or skin zone in the different layers of the well, for whose solution this work proposes the establishment of “flow stretches”. In this work, the term “flow stretch” is primarily used to differentiate sets of consecutive screens located at depths of the more permeable units (aquifers), among which there are other stretches mainly corresponding to less permeable units (aquitards). We have chosen to use the term “stretch” to avoid controversy with other terms such as “units”, which have a different hydrogeological meaning. Despite its origin, in this study, the term stretch is used to designate both the flow stretches in the well as well as the sets of layers to which they correspond. These stretches are obtained from a zonation process of the flowmeter log established by Díaz-Curiel et al. (1997), and it starts by generating a flow curve interpolated between water inputs. This curve is transformed into a smooth curve with constant depth increments. To obtain the depth values at which the limits between stretches are located, first the inflection points of the smooth curve are calculated and then the average values between those limits are determined. Finally, the upper and lower limits of each stretch of minimum values (the impermeable stretches) are approximated to each other, so that the average variance within each permeable stretch is minimal. These stretches show some parallelism with zonation relative to the average grain sizes shown in Díaz-Curiel et al. (1995), whose spatial extension is addressed in the discussion section. The use of the flow stretches allows the differences between screens within each stretch to be ignored, and their influence is not evaluated in this work because the average hydraulic conductivity of each flow stretch compensates for them.

Regarding the hydraulic interpretation of flowmeter logs, its main advantage
lies in the fact that different permeable layers that the well crosses may
have different hydraulic properties. These cannot be drawn from the results
of a conventional pumping test without using packers. The differences are
quantified by water inputs through screens corresponding to each layer and
its thickness. In wells with a high technical control budget, the hydraulic
characteristics of the different permeable layers can be achieved by using
packers. However, despite the high cost of this technique in deep wells, the
results do not have to match those obtained during operations with no
packers on the pump. The main reason for this difference is that, at higher pumping rates, there is significant vertical flow through the gravel pack
surrounding the screen (Boman et al., 1997). For example, for a well drilled
to 44.5 cm and cased with a 39.2 cm filtering pipe (annulus space
∼ 1400 cm^{2}) with a 2–3 mm gravel pack, the flow through it
is larger than the water inflow through an isolated screen of 320 cm (area
of ∼ 80 000 cm^{2}) located in front of sands whose
permeability is 100 lower. By isolating each layer, the static and dynamic water levels may be different from those presented in the well when
all permeable layers are connected (“dynamic level” refers to the well water
level when it reaches a quasi-steady state for a given pumping rate). The
influence of pump depth is not analysed in this study, considering that it
only affects the flowmeter logs mainly for measurements in front of the
screens close to the pump and that the initial study depths are rather below
the pump depth.

To achieve hydraulic interpretation from flowmeter logs, most authors (Molz
et al., 1989; Rehfeldt et al., 1992; Ruud and Kabala, 1996; Zlotnik and
Zurbuchen, 2003a; Barahona-Palomo, et al., 2011; Riva et al., 2012) start from the basis that hydraulic conductivity values for each permeable layer
(from each screen) are proportional to the hydraulic conductivity of the
entire well up to a multiplying constant. In these studies, the hydraulic
conductivity is obtained from measurements by a nearby piezometer during
pumping tests using the Theis equation (1935) between the discharge of a
well and the water level drawdown a short distance from the well (Theis,
1963). That proportionality is a function of the ratio between the water
input at each screen and the pumping rate and the ratio between the thickness of each screen and the saturated thickness of the aquifer. In
mathematical form, the hydraulic conductivity value of the permeable layer *j* is given by ${K}_{j}=(\mathrm{\Delta}{Q}_{j}/{Q}_{P})\cdot (\mathrm{\Delta}{z}_{j}/b)\cdot {K}_{P}$ (Kabala, 1994), where *Q*_{j} is the water input at layer *j*, *Q*_{P} is the extraction rate of the well, *b* is the aquifer
thickness, and *K*_{P} is the hydraulic conductivity of the entire well.
Among the different thicknesses in the literature, saturated thickness (Molz
et al., 1989; Li et al., 2008), aquifer thickness (Clemo and Barrash, 2003; Riva et al., 2012), and screened casing thickness (Barahona-Palomo et al.,
2011; Gueting et al., 2017) used to calculate the hydraulic conductivity of
an entire well, the saturated thickness is employed in this work.

Unlike the previous procedure, this study follows the less common
methodology established by Rehfeldt et al. (1989) starting from the Thiem
equation (1906). Although there are contradictory opinions on the validity
of this equation, some more recent studies consider that it is still
applicable for determining the hydraulic characteristics of the well
(Zlotnik and Zurbuchen, 2003b; Schneider and Attinger, 2008; Day-Lewis et
al., 2011; Houben, 2015). Rehfeldt et al. (1989) stated that a unique radius
of influence *R*_{0} value (the distance for which the produced drawdown in
the aquifer water table is nil) allows the direct determination of the
hydraulic characteristics of different permeable layers. Following the
proposal in Rehfeldt et al. (1989), variation in the radius of influence can
be neglected because it is included in the logarithm; therefore, its
variation affects the hydraulic conductivity computation by less than 10 %
for all permeable media in a given aquifer. This statement assumes that, for
a certain type of aquifer, its radius of influence varies by only a few hundred metres around a mean value of approximately 1000 m (Villanueva and Iglesias, 1984).

For these reasons, the goal of this work is to investigate the causes of
anomalies in the characteristic curves of pumping tests and to develop a
methodology that improves the estimation of the hydraulic parameters in
multilayered aquifers. Considering that the hydraulic conductivity (*k*) of the
permeable layers should remain the same at different pumping rates, this
advance is based on the fact that the hydraulic head of successive permeable
stretches can be different, as already proposed by Bennett and Patten (1960). Although different hydraulic heads are acceptable for determining the hydraulic properties of fractured aquifers (Hess, 1986; Paillet, 2000; Lane,
2002), this is not conventionally taken into account in multilayered
aquifers.

This methodology has been applied to a 475 m-deep borehole drilled in a multilayer detrital aquifer located in the centre of the Iberian Peninsula (Madrid basin). A step-drawdown pumping test was conducted in this well, showing discrepancies with Darcian behaviour and simultaneously with the non-Darcian coefficients of the Jacob equation. The relation between pumping rates and well drawdown in the step-drawdown pumping test as a whole did not show the expected behaviour for the type of aquifer considered. Moreover, the pump characteristic curves that were obtained do not correspond to any aquifer type. This difference results from the fact that the pumping rate increases with drawdown that has a power greater than 1 and that the specific obtained capacity increases with drawdown. A flowmeter log was collected, and the hydraulic interpretation is presented in this study, showing that the activation of the deepest aquifer stretches is the cause of this hydraulic behaviour, as explained throughout this study.

These results allow the avoidance of the possibly hazardous effects derived from intensive exploitation. As shown in this work, dangerously high arsenic contents occur in the deepest aquifer stretches in the Madrid basin (López-Vera, 2003). Since the studied well is part of the official network of the Madrid city water supply, it is imperative to limit the spread of this pollutant. As demonstrated by the hydraulic reinterpretation proposed in this paper, this aquifer undergoes strong activation when very high drawdown is applied, producing a sudden increase in its water inputs. This information is key to managing the exploitation network.

## 2.1 Estimating the hydraulic parameters

To determine the hydraulic conductivity *K* of the aquifer obtained through the
entire well and each permeable layer, the Thiem solution (1906) is used,
which is presented by Eq. (1) as a function of the radius of influence
*R*_{0}:

where *Q* is the extraction rate, *b* is the aquifer thickness, *d* is the drawdown in the well, and *r*_{w} is the well radius.

The main drawback to this procedure, which is mentioned by Kruseman and Ridder (1970), is the influence of local well factors on the drawdown values. Excluding friction along the pipe (which depends on depth), the different local well factors that modify the obtained hydraulic conductivity of the permeable layers are (1) the reduction in the cross-sectional area of the well due to the submersible pump, (2) the entrance loss caused by flow through the screen slots, (3) the head loss due to the gravel pack, and (4) the head loss caused by the disturbed zone around the well (referred to as the skin effect) (Hufschmied, 1986; Rehfeldt et al., 1989). Some of these factors have been considered in detail regarding flowmeter logs (Ruud and Kabala, 1997; Ruud et al., 1999). In this work, these factors are not considered because they do not justify an increase or decrease in the hydraulic conductivity with depth; thus, although any of the four factors may have locally different values, their influence on the hydraulic conductivity obtained at each permeable level is constant for any flow.

As established by Rehfeldt et al. (1989), the hydraulic conductivity of each permeable layer is given by Eq. (2):

where *q*_{j} is the water input produced in each screen, and Δ*z*_{j} is the thickness of each screen. Equation (2) has been applied in
various studies (Xiang, 1995; Oberlander and Russell, 2006), but in this
work, it is applied to well flow stretches.

## 2.2 Step-drawdown pumping test

In this type of pumping test, the hydraulic behaviour of the well is analysed through the characteristic relationship $d=A\cdot Q+B\cdot {Q}^{\mathrm{2}}$ (Jacob, 1947) or in a more general form (Rorabaugh, 1953), as shown in Eq. (3):

where *Q* denotes the consecutive values of the extraction rate in each step,
*d* is the corresponding stabilized drawdown (i.e. when its increase is negligible for an increase in the pumping time), *A* is a constant that
depends on transmissivity, and *B* and *p* are fitting constants to the
resulting data from the pumping test, where *p* is greater than 1 (Todd, 1980).
The second term represents the apparent divergence from the linearity
expected by Darcy's law (Darcy, 1856), which is addressed in Sect. 5. This is generally attributed to an increase in head loss due to turbulence
as the pumping rate increases. It is also coherent when the dynamic level
exceeds the depth of the upper aquifer layers, reducing the specific
capacity. Although some authors consider that the Jacob equation (Eq. 3)
can be improved, there are still authors who continue to use it (see Mathias
and Todman, 2010).

The conventional interpretation of step-drawdown pumping tests begins with the fact that drawdown for different pumping rates is caused by either the general or extensive characteristics of the aquifer. In this way, confined, semi-confined, and unconfined aquifers are distinguished, whose curves, pumping rate versus drawdown, and specific capacity versus drawdown are different in each case (Fig. 1).

## 2.3 Flowmeter data processing method

The need for an exhaustive treatment of the flowmeter logs arose initially to rule out the possibility that the anomalies observed in the characteristic curves of the step-drawdown pumping test could stem from the reliability of the flowmeter log results themselves. Thus, it had to be shown that such anomalies were not due to head losses along the well. In addition, considering that the flow velocity used in the Darcy–Weisbach equation is raised to a power of 2, the differences between the head losses resulting from considering the actual flow velocity instead of the velocity directly measured by the sonde are greatly amplified.

This exhaustive process of the flowmeter logs will be done according to the
laws of pipe hydraulics using the methodology developed by Díaz-Curiel
et al. (2020). To obtain the flow velocity at each depth, *<**V*(*z*)*>*, a conventional iterative process is used. It begins by taking the measured velocity *V*_{meas} at a given depth as the initial flow
velocity and the initial Reynolds number *R**e*_{ini} according to its
definition, that is, $Re=\mathit{\rho}\cdot \mathit{<}V\mathit{>}\cdot D/\mathrm{\mu}$, where *ρ* is the water density, *D* the well diameter,
and µ the dynamic viscosity. Then, the relationship *τ*(*R**e*) (see
Eq. 4) that provides the flow turbulence exponent *τ* as a function of
the Reynolds number is applied.

Knowing the turbulence exponent *τ* and the normalized radius *r*_{D} of
the sonde (the ratio of the sonde distance to the well axis with respect to
the well radius), a velocity law must be applied. This law is the ratio
between the velocity at the normalized distance *V*(*r*_{D}) and the maximum
velocity in the well axis *V*_{max} (see Eq. 5); this allows this maximum value to be obtained.

Then, using the relationship for the velocity factor *F*_{vel}(*τ*),
defined as the ratio between *V*_{max} and the flow velocity *<**V**>* (see Eq. 6), the first flow velocity is obtained with the corresponding Reynolds number *R**e*_{ini}, which is closer to the actual value.

Applying *τ*(*R**e*), *V*(*r*_{D}), and *F*_{vel}(*τ*), a new *R**e* value
*R**e*_{k} is obtained (*k* being the iteration index of the convergence
algorithm). This process is repeated until a given convergence criterion
${c}_{\mathrm{CR}}(R{e}_{k}-R{e}_{k-\mathrm{1}}\mathit{>}{c}_{\mathrm{CR}})$ is reached. The
process schematic is summarized in the flowchart in Fig. 2 (adapted from Díaz-Curiel et al., 2020) to obtain *R**e*(*z*).

In these equations, the influence of temperature is not considered because viscosity is practically homogeneous along the well due to water circulation during pumping.

Once the Reynolds number at each depth is known, the head loss can be
obtained by the Darcy–Weisbach equation (Darcy, 1857; Weisbach, 1845) given by $\mathrm{\Delta}h=f\cdot (\mathrm{\ell}/D)\cdot (\mathit{<}V{\mathit{>}}^{\mathrm{2}}/\mathrm{2}g)$, where *g* is the gravity acceleration (m ⋅ s^{−2}),
*<**V**>* is the average flow velocity (m ⋅ s^{−1}), *D* is the inner diameter of the well (m), ℓ is the length of each considered pipe
element (*m*), and *f* is the friction factor (dimensionless) for smooth pipes given by Eq. (7):

It is important to point out that, according to Eq. (7), as in all pipe hydraulics relations, the friction factor decreases with the Reynolds number, except for the transition interval between laminar and turbulent regimes.

Applying the rigorous formulation presented to process the flowmeter logs
(Eqs. 3 to 7) and considering that the sonde has a significant diameter
(*r*_{D}), the values of $\mathit{<}V\mathit{>}/V\left({r}_{D}\right)$ vary between 0.85
and 0.94. This difference represents a 20 % error in the total range of
variation of that velocity ratio between 0.5 for laminar flow and 1.0 for
fully turbulent flow. However, if the well diameter is smaller (close to the
diameter of the sonde), *V*(*r*_{D}) approaches *V*_{max}, resulting in the $\mathit{<}V\mathit{>}/V\left({r}_{D}\right)$ ratio presenting a greater variation (from
0.50 to 0.83) for the range of *R**e* found in the case studied than if the diameter of the well analysed is close to 0.2 m, as in the case studied in this work.

To estimate the hydraulic parameters from the flowmeter logs, once they have been processed, two specific approaches developed in this work are applied to obtain the actual hydraulic conductivity of the different layers. The first approach is to divide the well into flow stretches with different hydraulic behaviours as a function of the flowmeter results. The second approach is based on the fact that the hydraulic head of the deepest flow stretches of the well do not necessarily match the head of the overall well (Fig. 3).

The hydraulic head of a flow stretch is defined as its effective static level, that is, the height of the water level that would be achieved if the well were connected with the aquifer only through this stretch. This work proposes that a flowmeter log allows us to know the existence of hydraulic heads that are different for each stretch. This distinction implies changes in the effective drawdown of each stretch, which justifies, as shown in the case study, the water inputs of the deeper aquifer stretches not being proportional to drawdown.

In most works on hydraulic interpretation of flowmeter logs, a unique hydraulic head given by the static level *H*_{SL} of the entire well is
considered (Molz et al., 1989; Rehfeldt et al., 1992; Ruud and Kabala, 1996;
Zlotnik and Zurbuchen, 2003a; Barahona-Palomo, et al., 2011; Riva et al., 2012). Thus, the drawdown used in the Thiem (1906) equation is the same for
all of the aquifer stretches in a well, ${d}_{\mathrm{0}}\left(s\right)={h}_{\mathrm{DL}}\left(s\right)-{H}_{\mathrm{SL}}$,
where *h*_{DL}(*s*) is the dynamic level for the “*s*” pumping step and
*H*_{SL} is the dynamic level of the entire well. However, under the
hypothesis presented in this work, the hydraulic head of each stretch, and
therefore the corresponding drawdown, can be different. Numerically, the
drawdown of each flow stretch *T*_{N} will be given by the following
relation:

where *h*_{SL}(*n*) is the static level for flow stretch *T*_{N}. In
short, the proposed method consists of replacing the single drawdown *d* in Eq. (2) from Rehfeldt with a drawdown for each stretch.

The main differences with the method used by Paillet (1998) are that we have chosen to use the Rehfeldt relationship (Eq. 2) for permeability instead of the Davis and DeWiest relationship (1966) relation for transmissivity, given that the thicknesses of the layers and the productive sections are taken into account. The advantage of this option is that it is not necessary to know the storage coefficient of each contribution interval studied. It has also been considered that the different hydraulic heads are below the static water level (the water level in ambient conditions from Paillet, 1998). The procedure developed is based on the linearity of the hydraulic behaviour of the aquifer sections, and each section is treated separately.

The proposed method for obtaining the hydraulic head of each flow stretch is
to (1) correct the drawdown values of the total head loss due to flow along
the pipeline and (2) modify the height of the hydraulic head for each flow
stretch until the straight line fitted to the data, *q*_{N}(*s*) versus
*d*_{N}(*s*), reaches the maximum regression coefficient (where *q*_{N}(*s*) is
the water input in flow stretch *N* for the *s* pumping steps). With a static
level value for each flow stretch, the effective drawdown of each flow
stretch can be obtained, and although other local well factors may cause
differences between screens within each stretch, their influence is not
evaluated in this work because the average hydraulic conductivity of each
flow stretch compensates for them.

## 4.1 Geology of the area and well characteristics

The study well (named CNC in this work) is located in the Tagus River basin in the Iberian Peninsula. More specifically, it is located in the western sub-basin, also known as the Madrid basin, near the city of Madrid (Spain). The Madrid basin has a triangular shape and is bound by several mountain ranges, the “Central System” of the Iberian Peninsula of igneous–metamorphic nature, located north-west of the Madrid basin and the main contributing source area (Fig. 4). The structure of the basement corresponds to that of a complex graben and has resulted in a sediment thickness of approximately 1000 m, although in some areas, the thickness can exceed 3000 m. The Tertiary (Miocene) sediments that fill the basin correspond to continental deposits of an arid, endorheic nature that are fed by alluvial fans; these alluvial fans develop edge or detrital facies, intermediate or transitional facies, and central facies, all of which are characteristic of this depositional system (Navarro et al., 1993).

The aquifer is located in the continental siliciclastic basin of Madrid, which in the literature is separated into two lithostratigraphic formations differentiated by grain size and, therefore, by hydrogeological characteristics; due to the depositional process of the materials, they are differentiated from one area to another as well as vertically. The lower formation is composed of arkose that is generally very clayey with clayey sand. The upper formation consists of arkosic coarse-grained sand, gravel, and clay. Although the upper formation is sandier and permeable and overlaps the more clayey lower formation, they are not considered different aquifers (López-Vera, 1985) but rather a heterogeneous and anisotropic free aquifer system where more permeable layers are separated by clayey strata with a lower permeability (which qualifies as a multilayer aquifer).

A lithological column was compiled from information provided by the detritus from the borehole and conventional well logs: normal resistivity and natural gamma ray logs, which are presented in Fig. 5. Note that the logs were not corrected for borehole diameter, conductivity, or mud density; therefore, there was a notable difference between the larger diameters in the upper part and the base. Three differentiated parts were established: the first (0 to 75 m) was composed of sands alternating with thin layers of clay, the second (75 to 285 m) comprised alternating sandy clay and thin sandy layers, and the third (285 to 485 m) had a predominance of coarse sand and gravel with intercalations of very thick clay layers. As a result of the correlation between lithological stretches in the north-western zone of the studied basin (Díaz-Curiel et al., 1995), the permeable stretches can be considered radially homogeneous differentiated aquifers. With the exception of the superficial part, the rest of the permeable stretches can be treated as confined aquifers. This allows the use of the Thiem equation for these stretches and for obtaining hydraulic parameters on a regional scale (as proposed by Rehfeldt) by averaging the stretches as a whole (Sánchez-Vila, 2006).

The borehole was rotary drilled with a diameter of 660 mm down to a depth of
120 m, and then it was drilled with reverse injection of natural mud with a
diameter of 445 mm to a final depth of 490 m. The construction details of
the well consisted of casing to a depth of 480 m, with a 404 mm inner
diameter in the sections of blind pipe and 392 mm in the wire-wrap screen sections; a gravel packing of 2–3 mm grains was added throughout its length.
The well was developed by adding previously diluted polyphosphates, and
after 12 h, a series of intermittent pumping was carried out; once the
extracted water contained no suspended fines, a 72 h gauging of
increasing pumping was conducted up to a flow rate of 100 l s^{−1}.

## 4.2 Pumping test results

After a process was conducted to eliminate the well storage effect, the
static level settled at a depth of 151 m. The pumping test started with a
flow of 5 l s^{−1} until the hydraulic head stabilized. Two main extraction
pumping rates of 30 and 70 l s^{−1} and a final rate of 75 l s^{−1} were then used, with a total elapsed time of 80.5 h. All steps were performed for a
sufficient time to reach the quasi-steady conditions mentioned in Sect. 1. The resulting temporary data are shown in Fig. 6, and the drawdown values for each pumping rate are shown in Table 1.

Hydraulic conductivity values were obtained using Eq. (1) (Thiem, 1906), taking the saturated thickness to be equal to 329 m (the depth of the well minus the depth of the static level) and considering a radius of influence of 950 m once the quasi-steady state was reached. This last datum is the central value of those shown in Villanueva and Iglesias (1984) for semi-confined and confined aquifers. The resulting hydraulic conductivity values of the well are shown in Table 1, and they increase with drawdown.

The hydraulic conductivity values that were obtained do not have to coincide
with the general values of the aquifer (since the general values of the well
also depend on the construction details) or with those obtained for each of
the different permeable stretches that the well crosses (since the result
for the well is an average behaviour of those flow stretches). However, it
is possible to speak of a mean value (geometric average) of approximately
$\mathrm{3.9}\cdot {\mathrm{10}}^{-\mathrm{4}}$ Darcy. To hydraulically characterize the well from the pumping test results, Fig. 7 shows the pumping rate versus drawdown
*Q*(*d*) and the specific capacity versus drawdown $Q/d\left(d\right)$.

Let us remember that in the characteristic equation $d=A\cdot Q+B\cdot {Q}^{p}$ for the well for step-drawdown pumping tests, the
first term corresponds directly to Darcy's law (1856) for the total volume
of the water flow crossing through successive cylindrical layers. In the
second term, the exponent *p* can be greater than 1; successive drawdown should
show a power relationship with an exponent greater than 1 versus the pumping
rate. Moreover, the specific capacity should decrease with successive
drawdown; otherwise, the well extraction ratio would increase with drawdown.
However, in Fig. 7, the opposite pattern is observed; i.e. *d*(*Q*) increases with a power that is less than 1, and $Q/d$ increases with drawdown. These
anomalies do not seem to arise from errors in the water level measurement,
as their values versus time appear to be correct (Fig. 6).

## 4.3 Flowmeter results

The static level *H*_{SL} was measured at a depth of 157 m before the
beginning of flowmeter logging. Flowmeter logs were obtained for pumping
rates of 20 l s^{−1} (measured dynamic level at 172 m), 30 l s^{−1} (dynamic level at
178 m), and 70 l s^{−1} (dynamic level at 205 m). The drawdowns of the entire
well for each pumping rate, without including the head losses, hence are 15 m, 21 and 58 for 20 l s^{−1}, 30, and 70, respectively.

Since the flowmeter logs (spinner type) were collected during pumping
operations, measurements could be obtained only below the pump depth. For
the pump located at a depth of 191 m, logs were recorded from 200 to 470 m
for pumping rates of 20 and 30 l s^{−1}, and for the pump located at 253 m, logs
were recorded from 260 to 470 m for pumping rates of 30 and 70 l s^{−1}. The
logs were obtained with an average sampling rate of 33 cm. Once calibration
has been applied, the velocity obtained is averaged from the top of each
screen to the bottom of the next, obtaining the values at 40 depths that
appear in the raw data.

Equation (5), that of $V\left(r\right)/{V}_{\mathrm{max}}$, used a normalized distance of 0.64, which
corresponds to the ratio (${r}_{\mathrm{w}}-{r}_{\mathrm{s}})/{r}_{\mathrm{w}}$, where *r*_{s} is the
external radius of the spinner frame (the sonde has a device that maintains
its hold on the wall) and *r*_{w} is the inner radius of the well casing. The
different diameters (difference *<* 1 %) in the screens were not
considered due to the difficulty of executing the iterative process to
obtain *<**V**>*. The initial velocity values considered in the iterative process were obtained by applying the calibration curve to the
velocities measured by the sonde. The initial *R**e* values varied between 860
and 211 000 for all flow rates and pumping rates. For *τ*(*R**e*), Eq. (4),
the resulting values of the turbulence exponent varied from 1.0 to 6.7,
resulting in values of $\mathit{<}V\mathit{>}/V\left({r}_{D}\right)$ between 0.85 and
0.94. The velocity factor values determined using Eq. (6) were in the range
of 0.50 to 0.83, and deviations with respect to the average value reached
35 %. In addition to the zone where the studied well is located, there is
no geothermalism at all, and the influence of temperature is not considered, as in the common equations on the hydraulic characterization of aquifers.

Figure 8 shows the results obtained for the main parameters and ratios of processing flowmeter logs by applying the methodology of Díaz-Curiel et al. (2020).

The accuracy of the measuring equipment was 0.5 l s^{−1}, which greatly reduced
the reliability of the results between consecutive screens and produced
strong variation in the quantified water inputs from each screen.

## 4.4 Head loss results

The head loss was calculated using the Darcy–Weisbach equation (Darcy, 1857; Weisbach, 1845), and the friction factor was calculated using Eq. (7). The
curve of the friction factor values obtained for pumping rates of 20, 30,
and 70 l s^{−1} is shown in Fig. 8. Depending on the scale on which the
transition interval is analysed, the turbulence of the fluid flow cannot be
determined at all points along its path. In this study, we chose to use a
fitting expression for smooth pipes given by Eq. (7) because the flowmeter
sondes used in well logging reflect the fluid advance on a much larger
scale. The friction factor for low pumping rates in the deep screens
increased by a maximum of 70 % compared to that obtained using
conventional equations.

The total head loss below the pump is obtained by integrating the head loss
throughout the well based on the flow velocity obtained at each depth (see
Fig. 8); that is, the cumulated Δ*h* adding the successive local head loses values relying upon local friction factors and local water velocities.
Above the pump depth, the calculation is based on a linear increase in the
velocity between the pump depth and the dynamic level. The obtained values
of the head loss Δ*h*(*s*) for each pumping rate are shown in Table 2,
which will be used in the calculation of the effective drawdown produced.

In this case, the friction factor reaches values 6 times higher at the bottom of the well than at the initially recorded depth, and the value of the head loss is low (0.06 m), because the average velocity in the Darcy–Weisbach equation is raised to a power of 2. Therefore, in large-diameter water wells, the influence of the friction factor along the pipeline is negligible. Finally, despite the inclusion of head loss values, the water inputs from some of the stretches still do not maintain the expected proportionality with drawdown, so hydraulic reinterpretation is carried out using the flowmeter results.

## 4.5 Water inputs

Figure 9 shows the results from different pumping rates after processing. On the left-hand side of Fig. 9a, the curves for upward flow rates versus depth are shown, and in Fig. 9b, the water inputs deducted in the different screens are shown, while the negative water inputs (outputs) are not shown in Fig. 9b.

Note that the accuracy provided by the equipment is 0.05 l s^{−1}, which greatly
reduces the reliability of the results between consecutive screens and
produces strong variations in quantifying the water inputs from each screen.
For this reason, following the criteria described in Sect. 3, the flowmeter log is divided into different flow stretches based on the average
productivity of each flow stretch.

Table 3 shows the water inputs from the different flow stretches for each
measured depth interval. A “top” stretch has been added to the top of the
well above the pumping depth, where the different water inputs are unknown.
The water input in the upper part (which includes flow stretch *T*_{1} for
the case of a pumping rate of 70 l s^{−1}) is obtained by the difference between
the pumping rate and the deduced flow rate at that depth.

At a pumping rate of 70 l s^{−1}, the water input from flow stretch *T*_{1} is
not known, and the input of this flow stretch may increase in proportion to
the pumping rate, which should imply that the upper part of the well would
remain constant (e.g. due to the dynamic level dropping below some of the upper layers).

Both Fig. 9 and Table 3 show that the water input from flow stretch *T*_{2}
is very low, even for high pumping rates, and it is close to the flowmeter
accuracy; hence, that flow stretch is omitted from the analysis.

Table 3 shows that for pumping rates of 20 and 30 l s^{−1}, the water inputs from
the upper part of the well and from flow stretches *T*_{1}, *T*_{3}, and
*T*_{6} increase in a way that is practically proportional to the flow (with
a ratio ≈1.5) and fits a confined aquifer. Flow stretches *T*_{4}
and *T*_{5} have negligible water inputs, reaching negative inputs for a
pumping rate of 20 l s^{−1}. However, for the 70 l s^{−1} pumping rate, there is an
abrupt change in the hydraulic behaviour of the well. On the one hand, the
whole water input from the upper part of the well and from flow stretch
*T*_{1} does not increase proportionally to the pumping rate (ratio = 2.33). On the other hand, flow stretch *T*_{6} shows a sharp increase in the water
inputs, and flow stretches *T*_{4} and *T*_{5} present an apparent
activation. Given the possibility that an increase in the head loss could
justify such behaviour, values for each pumping rate were calculated and
added.

The high correlation of the water inflows in stretches 2 and 3 for the pump located at the depths of 191 and at 253 m confirms the consideration that the depth of the pump does not affect the values obtained with the flowmeter logs.

^{a} As cited above, this flow stretch is not analysed because its water inputs are very low for all pumping rates.

Regarding the existence of different hydraulic heads, note that the negative
water input in flow stretches *T*_{4} and *T*_{5} for the pumping rate of 20 l s^{−1} corroborates the validity of the hypothesis in this work. These negative
inputs reflect the fact that when the drawdown is located above the
hydraulic head of these flow stretches, the water flow does not occur
inwards towards the well but rather outwards, reducing the upward vertical
flow. In any case, the fact that the deeper flow stretches have a hydraulic
head below the static level of the well explains why the pumping rate versus drawdown curve adjusts to a power function with an exponent greater
than 1, and the specific capacity versus the drawdown curve is ascending. There are several studies in the literature that mention negative water inputs as
those obtained in this case, but they do not present the hydraulic
interpretation thereof; most of them correspond to flow logs measured in ambient conditions (Paillet et al., 2000; Butler et al., 2009; Day-Lewis et al., 2011).

## 4.6 Hydraulic reinterpretation

The permeability of each stretch has been calculated using Eq. (2). Instead
of the contribution of each layer *q*_{j}, the sum total of the contributions
of each stretch *q*_{N}(*s*) is considered (see Table 3). The unique initial
drawdown *d* considered in Eq. (2) has been modified by the drawdown of the
entire well ${d}_{\mathrm{0}}\left(s\right)={h}_{\mathrm{DL}}\left(s\right)-{H}_{\mathrm{SL}}-\mathrm{\Delta}h\left(s\right)$ for each
pumping rate (*s*) (Δ*h*(*s*) being the head losses shown in Table 2). The static level *H*_{SL} is 157 m (as determined before the flowmeter logging
was conducted) and the dynamic levels *h*_{DL}(*s*) are 172 m for a pumping rate of 20 l s^{−1}, 178 m for a pumping rate of 30 l s^{−1}, and 205 m for a pumping rate of 70 l s^{−1}. The thickness of each layer Δ*z*_{j} has been replaced by the
thickness of each stretch Δ*z*(*T*_{N}) (depth intervals in Table 3).
The radius of influence (*R*_{0}) considered is 950 m (as in the previous
calculations), and the well radius (*r*_{w}) is $\mathrm{0.404}/\mathrm{2}=\mathrm{0.202}$ m. The
characteristic curves of each stretch are shown in Fig. 10a.

Analysing the specific capacities of different flow stretches, *T*_{1} and
*T*_{3} show the expected proportionality for a confined aquifer. However,
this is not the case for flow stretches *T*_{4}, *T*_{5}, and *T*_{6}, whose
*d*_{N}(*s*) versus *q*_{N}(*s*) data fit to a power function with exponents of
0.22, 0.37, and 0.67, respectively (see Fig. 10a). Not only does this not
reflect Darcian behaviour, but it also indicates an exponent *p* in the Jacob equation of less than 1, as is the case with the well as a whole (see Fig. 7).

However, if it is considered that flow stretches *T*_{4}, *T*_{5}, and
*T*_{6} have different hydraulic heads, the results vary. Through an
iterative process, the value of the static level (hydraulic head) of each
flow stretch for which the total water input of the flow stretch versus the
drawdown acquires greater alignment can be determined. This means that when
the data are fitted to a straight line, the regression coefficient is
maximum. In other words, the resulting exponent in the Jacob equation when
the data are fitted to a power function is *p*=1. Thus, for flow stretch
*T*_{6}, the static level for which inputs versus drawdown acquire greater
alignment occurs at a depth of 165 m. Similarly, the resulting static level
for flow stretch *T*_{5} is located at a depth of 175 m. For a pumping rate
of 70 l s^{−1}, flow stretch *T*_{4} undergoes an “activation” effect (even
higher than flow stretch *T*_{5}) when the dynamic level exceeds the true
static level of *T*_{4}, which is computed at a depth of 177.5 m.
In summary, the hydraulic heads *h*_{SL}(*N*) obtained with this criterion are 157 m for *T*_{1} and *T*_{3}, 177.5 m for *T*_{4}, 175 m for *T*_{5}, and
165 m for *T*_{6}.

Figure 10b shows the regression lines of water inputs versus drawdown for
each stretch, with the corresponding relationships and *R*^{2} coefficients.

With these differentiated static levels, the hydraulic conductivities of
each flow stretch were obtained using a next change of Eq. (2) (Rehfeldt et
al., 1989) replacing *d*_{0}(*s*) with ${d}_{N}\left(s\right)={h}_{\mathrm{DL}}\left(s\right)-{h}_{\mathrm{SL}}\left(N\right)-\mathrm{\Delta}h\left(s\right)$, whose values are presented in Table 4.

The successive relationships used to arrive at the actual permeability with depth have been

It must be pointed out that *k*_{N} is the same for the different (*s*) because the ratio ${q}_{N}\left(s\right)/{d}_{N}\left(s\right)$ is the same for any pumping rate (*d*_{N}(*s*)
versus *q*_{N}(*s*) are fitted to a straight line).

The average hydraulic conductivities of the stretches in the studied part of the well (200 to 470 m) have values between $\mathrm{2}\cdot {\mathrm{10}}^{-\mathrm{4}}$ and $\mathrm{1.3}\cdot {\mathrm{10}}^{-\mathrm{3}}$ Darcy, providing a geometric mean value of $\mathrm{5}\cdot {\mathrm{10}}^{-\mathrm{4}}$ Darcy, which is close to the average hydraulic conductivity obtained with the pumping tests. The largest contrast occurs with the difference between the hydraulic conductivity values of the different flow stretches, which is close to an order of magnitude.

As mentioned at the beginning of Sect. 4, the precision of flowmeter logs does not allow us to obtain reliable hydraulic conductivity values of each permeable layer to make a more detailed characterization of each stretch. However, that analysis could be undertaken by considering the average water input and average thickness.

Regarding the linearity predicted by Darcy's law, in this work, the
variation corresponding to non-linear flow is a different process than the change in the flow from a laminar to turbulent regime. Takhanov (2011) determined that the onset of non-linear flow occurs prior to the change to turbulent flow; in fact, some authors have considered that turbulent flow
does not occur in porous fine-grained media in their natural state (Green
and Duwez, 1951; Bakhmeteff and Feodoroff, 1937). In this sense, Houben (2015) established a linear laminar regime in the aquifer that becomes
non-linear in the gravel pack and only becomes turbulent on the screen and inside the pipe. In this work, the regime change is less gradual than that
predicted by the Forchheimer equation (1901) and does not increase with the
same power after the transition. It should be taken into account that both
the values of the friction factor and the particle Reynolds number
established for the Forchheimer flow decrease as *R**e* increases. To analyse
the flow linearity in water wells, the hydraulic characteristics of the flow
in the aquifer levels must be quantifiable by the velocity near the well.
Moreover, a value of 0.01 m s^{−1} can be considered the maximum velocity in
groundwater near wells. For example, if a water well with a very high
extraction rate of 100 l s^{−1}, radius of 0.2 m, total length of 400 m, and screened length of 80 m (20 %) is considered, then the average water input
velocity would be 0.005 m s^{−1}. Considering the results in van Lopik et al. (2017),
non-linear behaviour starts at velocities greater than 0.01 m s^{−1}, so the maximum water input still exhibits Darcian behaviour.

Among the possible explanations for the difference in hydraulic head values
for the deeper flow stretches are hydrogeological reasons, such as the
presence of flow stretches with different vertical transmissivities.
However, the approximated values for the hydraulic conductivity in the less
permeable stretches (*T*_{2} and *T*_{4}) contradict this hypothesis, since
flow stretch *T*_{2} is less permeable than flow stretch *T*_{4}, but flow
stretch *T*_{3} is not affected by a similar effect. Another possible
explanation is that the change in the effective drawdown is due to the
existence of nearby extraction wells, which overexploited the aquifers
corresponding to flow stretches *T*_{4} and *T*_{5}, thereby producing a
drop in the static level of these flow stretches.

Concerning the reliability of the final permeability values, one aspect that must be considered in estimating hydraulic parameters from flowmeter results is that the analysis was conventionally performed through the screens assembled in the casing. However, the distribution of these screens only approximately matches the permeable layers that the well crosses. Hence, differences between the thicknesses of the permeable layers and the assembled screens may exist as well as permeable layers that are not faced with a screen, whose effects are minimized by gravel packing. This effect adds to that produced by the local factors of the aforementioned well, which is an additional reason for differences in the water inputs of the different screens within each stretch.

Therefore, although the results of the pumping tests and the flowmeter results yield a similar hydraulic conductivity value for the entire well, after considering the possible hydraulic head difference that justifies and relates the anomalies reported over the pumping test data, this value moves away from the actual hydraulic conductivity of the aquifer.

Under the consideration that vertically there is a high hydraulic connection (similar to the horizontal one), it is common practice in hydrogeology to model large aquifers as an equivalent porous medium. In addition to obtaining water balance results, such models have a wide application in many basins (De Filippis et al., 2016). However, this study focuses on a case where the vertical hydraulic connection is much lower than the horizontal one, as can be deduced from the existence of the different hydraulic heads found. In this study, it is considered that the low hydraulic connection due to the existence of one or several wells in a basin of the size studied does not significantly affect the lateral variations of the hydraulic head along the basin. In contrast with several works taking into account the hydraulic head field (Yeh et al., 1996; Axness and Carrera, 1999), in this study it is considered a single hydraulic head for distances smaller than the radius of influence. When wells are continuously screened, on a small scale it can be taken into account that the hydraulic head does not show as abrupt a change, as is considered in great continental hydrological basins. In these basins this effect, which causes the conventional hydraulic head field over distance, is included in the hydraulic parameter relationships from the hydraulic head gradient. It is also considered that, in the interior of a large-diameter well, such as water wells in large continental basins, there is no change with depth of the effective hydraulic head. In oil wells, this possibility is considered because of the strong variations in vertical flow velocity and the use of smaller diameters, leading to higher head losses.

Regarding Jacob's well equation (Eq. 3), some authors say that the
coefficient that multiplies *Q*^{2} is the turbulent flow coefficient, but
others say that when the characteristic curve is not linear, it is because
turbulent flow occurs. However, it is not clear what this “turbulent flow”
refers to. It does not seem to refer to the change in flow in the pipeline
but to the water in the aquifers acquiring turbulent flow. Regarding the
friction factor, water flow in granular aquifers is not turbulent, although
the obtained *R**e* value would correspond to turbulent flow if the thickness of
the aquifer is used to calculate the Reynolds number instead of using a mean
pore diameter through which the water circulates.

This contrasts with the complex flow regime in oil wells where gas and
liquids of different characteristics are combined, the behaviour of which
has been analysed in many publications (Nind, 1965; Hasan and Kabir, 1988;
Brill and Arirachakaran, 1992; Kabir and Hasan, 2006; Wu et al., 2017). This
may lead one to believe that such behaviour is also common for water.
However, if we consider, for example, a pressure gradient reaching 5 atm and
an average pore diameter reaching 2 mm, the *R**e* number obtained for water
flow is *<*100, which does not correspond to turbulent flow.

Related to the spatial extension of the different hydraulic heads obtained, there are two facts that should be considered. On the one hand, hydrogeologists who have studied the Madrid basin are already aware of the increase in arsenic that occurred at other points in the north-western part of the basin for high drawdowns (López-Vera, 1985). This would confirm that the hydraulic head of the arsenic-contaminated stretches is lower. On the other hand, although, as already mentioned, this part of the basin is classified as a heterogeneous and anisotropic-free aquifer system (Samper, 1999; Yélamos and Villarroya, 2007), other studies on borehole correlation in this area show that the stretches established from logs reach distances of more than 10 km (Caparrini, 2006).

This study has allowed us to carry out the hydrological and hydraulic division of the studied basin that had not been done before, and such division involves more precise obtaining of the permeability values in each stretch (and hence in its corresponding aquifer), which was not been done before. Certainly, the new procedure developed to obtain the hydraulic head differences in heterogeneous granular basins and the results obtained for the first time in the Madrid basin may allow hydrogeological hypotheses to understand the large-scale structure of aquifers concerning recharge. According to the results obtained, the fact that the Madrid basin is considered a single aquifer should be replaced, at least from a depth of 200 m, with a sequence of stretches – aquifers – differentiated by their different permeability values. From 345 m depth (the one of stretch 4), it was also found that the aquifers corresponding to stretches 4, 5, and 6 have different “hydraulic heads” than the upper aquifers. One hypothesis would be that this means different “recharge pathways”, so that it could be deduced that, above 345 m, the Madrid basin can be considered a single heterogeneous aquifer (with different sub-aquifers of different permeability), and below 345 m, the Madrid basin consists of a sequence of confined aquifers (the last three coarse-grained ones shown in the well logs; see Fig. 5) that are hydraulically separated from the rest of the aquifers.

The described results can be added to the conceptual models developed both from Toth's (1962) scheme (López Vera et al., 1977; Navarro et al., 1993; Heredia et al., 2001; Martínez-Santos et al., 2010) and from the more recent models on the flow model considering the land subsidence obtained by the A-DInSAR technique (Ezquerro et al., 2014; Béjar-Pizarro et al., 2017; Boni et al., 2020). It should be emphasized that the hydrogeological hypotheses that can be made as the scheme included in Fig. 11 must be contrasted with results in more wells within the siliciclastic basin of Madrid. The usual sub-division of this basin (which forms part of the Tagus basin) is into the lower and upper formations, whose contact according to the hydrogeological map (scale 1:200 00, IGME, 1991) of the Spanish Geological Survey is “gradual and arbitrary” and therefore does not provide information on their depth. However, according to the correlation sections of the well logs shown in Caparrini (2006), the bottom of the coarser-grained upper formation is located above the depths analysed in the studied well. It should be noted that the same fact occurs with the hydrogeological models of the Madrid basin, in which the variations in the water table are far above the upper depth analysed in the studied well. In this sense, the hypothesis that can be put forward on the basis of the data from the analysed well is that, within a radius of 10 km around the well, a hydraulic differentiation must be considered from a depth of ∼ 200 m onwards.

The division of the studied well also allows us to propose a strategy regarding the arsenic propagation in the Madrid basin. The obtained results indicate that the stretch of the studied well that is “activated” when the dynamic level exceeds the “hydraulic head” of the aquifer to which it corresponds is rather connected to a point – or zone – where the arsenic focus is. As the exploitation of that stretch in different points of the basin will cause the contaminant to move towards those points, that critical dynamic level should not be allowed.

Finally, regarding the application of this methodology to other aquifers of the same type, there is no hydrogeological hypothesis that implies that in other great continental basins in which large impermeable-type stretches are found, all the permeable stretches should have the same hydraulic head.

The improvements developed in this work are represented by the following advances in the hydraulic interpretation of flowmeter logs.

- a.
The method developed from the flowmeter allows us to reinterpret the hydraulic behaviour of any well in which the characteristic curve

*d*(*Q*) increases with a power less than 1 and the characteristic curve $Q/d$ increases with drawdown, which until now was considered anomalous due to poorly measured data or due to changing aquifer characteristics with pumping time. - b.
The processing of flowmeter logs provides an increase in the quantified values of water inputs in the deepest permeable media for low pumping rates. This increase modifies the obtained values for hydraulic conductivities in the studied well data that approach Darcian behaviour but do not reach it.

- c.
The division of the wells into flow stretches with different hydraulic heads provides hydraulic reinterpretation that explains the possible anomalies produced in the step-drawdown pumping tests. As occurs in the well in this study, both the characteristic curve of the pumping test and the specific capacity versus the drawdown curve show unexpected slopes, the anomalous nature of which is not justified by non-Darcian behaviour.

- d.
In particular, the resulting values of the different hydraulic heads make it advisable, in any well located in the Madrid basin, not to use pumping rates for which the dynamic level goes beyond the depth corresponding to the drawdown of 165 m in the studied well. Once it is determined whether flow stretches

*T*_{4}and*T*_{5}have a greater arsenic content than flow stretch*T*_{6}, the mentioned depth can be changed to that corresponding to a drawdown of 175 m in the studied well.

The verification of the existence of different hydraulic heads for the different stretches with depth entails a substantial change in the hydrogeological knowledge of a basin such as the one studied. It can also be concluded that the corresponding determination of the actual hydraulic properties of the different stretches is essential for modelling the hydraulic behaviour of the basin. Likewise, although it does not have a spatial extension corresponding to the entire basin (as there are characteristics that do not necessarily have to be maintained, depending on the position with respect to the different source areas and the distance to them), the extension of up to 10 km is sufficiently interesting to characterize parts of the basin.

As a future line of action, this study proposes the execution of step-drawdown pumping test and flowmeter logs with various flow rates in wells progressively distant from the studied one to verify the stretches with different hydraulic heads and to determine the spatial extension of this behaviour.

The data used in this paper are available for download at the following link: https://data.mendeley.com/datasets/gx8dwgvygn/1 (Díaz-Curiel, 2020).

JDC conceptualized the paper. JDC developed the methodology. JDC and MJM contributed to the writing of the paper, with BBV and LAL reviewing and editing the paper. JDC and NC curated the data and led the investigation. BBV and LAL did the formal analysis and prepared visualization data. JDC supervised the project.

The contact author has declared that neither they nor their co-authors have any competing interests.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The authors would like to thank Canal de Isabel II (Madrid, Spain) for the permission to use the flowmeter logs and the provided information on the pumping test as well as Springer's language service for the editing of the manuscript (for correctness of the English language, grammar, punctuation, spelling, and general style).

This research has been supported by the Comunidad de Madrid (grant no. P2018/EMT-4317).

This paper was edited by Mauro Giudici and reviewed by four anonymous referees.

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