TECHNICAL FIELD
The subject matter described herein, in general, relates to shaly reservoirs and, in particular, relates to a method for evaluation of water saturation of a shaly reservoir. BACKGROUND
Upstream petroleum industry operations involve drilling of boreholes and wells to explore a unit of litho-stratiography i.e.an earth formation for the presence of hydrocarbons and subsequent exploitation. The evaluation of hydrocarbon content of hydrocarbon bearing reservoirs requires knowledge of several fundamental reservoir properties including water saturation. Water saturation is the fraction of water in a given pore space of a reservoir rock. Likewise, the fraction of hydrocarbons in the given pore space of the reservoir rock is termed as its hydrocarbon saturation.
Generally, the quantitative calculation of hydrocarbon content of a reservoir is performed by first calculating water saturation of the reservoir. The water saturation is calculated using various log data such as electrical resistivity, bulk mass density, hydrogen index, sonic wave velocity, and natural gamma ray (GR). The log data is typically used with theoretically and empirically established relations based on various saturation equations to compute the water saturation.
Conventional saturation equations, such as Archie's saturation equation
(Equation Removed)conductivity of the reservoir, Cw is conductivity of
the formation water, n is saturation exponent, SK is water saturation of an un-invaded
zone of the formation, and F is the formation resistivity factor), when applied to calculate the level of water saturation have only been useful in the analysis of clean or high resistivity reservoirs, i.e., reservoirs with no or minimum clay content. However, such conventional equations have found little application in the analysis of low resistivity shaly reservoirs, i.e., reservoirs with considerable clay content. The clay or clay minerals in the reservoirs provide an additional conducting path besides the conducting path provided by water, thereby reducing the resistivity of the reservoirs to such an extent that it becomes difficult to distinguish hydrocarbon bearing zones from water bearing zones. The Archie's equation assumes that the only conducting constituent of a reservoir is the formation water. It does not account for any additional conductance due to the clay minerals in the shaly reservoirs.


In order to accommodate excess conductivity due to shaliness of a reservoir, various evaluation models have been established. One such class of models includes shale volume (VSh) models. In the shale volume models, the quantity VSh, which is the volume of wet shale per unit volume of reservoir rock, is computed with the help of different logs like GR, spontaneous potential (SP), resistivity, neutron-density combination, etc. The shale volume models assume that the effect of shale laminations or authigenic clay on the overall electrical conductivity of the reservoir is proportional to the volume fraction of the shale irrespective of its type and distribution.
The log measurements used for VSh computations are independent of distribution, morphology of shale or clay minerals in the reservoir, and interrelationship of shale or clay minerals with pore fluids on which the resistivity measurement basically depends. Further, these models assume that the clay minerals present in the shaly reservoirs are same as those present in underlying or overlying shale bed, and are referenced for computation of volume and conductivity of the shaly reservoirs. Additionally, such models assume that the sand fractions other than the shale laminations are clean. However, the above mentioned conditions are seldom true. Thus, in the conventional shale volume models, the model information typically indicates the volume of the shale, thereby ignoring the effect of clay distribution and clay type.
Another class of models established to accommodate the excess conductivity due to shaliness is based on Ionic Double Layer (IDL). The petro-physical models, based upon the IDL phenomenon, account for the presence of dispersed clay. According to these models, the abnormal conductivity of a shaly reservoir containing an electrolyte is the consequence of an ionic double layer of the solution adjacent to a clay surface or a clay coated sand grain surface. The effect of the ionic double layer is quantified by an electric shale parameter Qv. The electric shale parameter Qv is multiplied by equivalent conductance of clay counter ions B to get clay conductivity

The electric shale parameter Qv can be determined from pulverized core samples through chemical titrations in a laboratory. However, such core samples are often not representative of the reservoir as a whole. Furthermore, even if the values of the electric shale parameter Qv at specific depths of the reservoir from where the


samples were taken are known, the calculation of the hydrocarbon saturation is subject to large errors if in-situ water content of the reservoir is fresh i.e. has low salinity. Moreover, during the pulverisation process, the native cation exchange capacity gets modified due to additional broken bonds.
Therefore, in-spite of being theoretically exact and experimentally established, the IDL models have not been extensively put into field applications due to lack of continuous downhole measurement of clay conductivity Ce. Further, evaluations
using the conventional log measurements are typically done assuming a particular type of shale distribution model and incorporating assumptions into the model information. The formation resistivity thus estimated can be typical of a water bearing reservoir even though the sand laminae actually produce hydrocarbons. SUMMARY
The subject matter described herein is directed to a method and system for determining effective water saturation of a shaly sand reservoir.
According to an embodiment of the present subject matter, an initial water saturation of a shaly reservoir is determined. A spontaneous potential (SP) log is recorded in a borehole in the shaly reservoir drilled with a saline drilling mud. The saline drilling mud includes an electrolyte such that spontaneous potential along the depth of the borehole is substantially equal to membrane potential along the depth of the borehole. The recorded SP log is normalized to compensate for the bulk nature of clay or clay minerals present in the reservoir.
The normalized SP log, along with the initial water saturation, is utilized to compute effective water saturation of the shaly reservoir. The estimated effective water saturation compensates for the volumetric nature, type and distribution of the clay minerals, and the chemical environment. In one implementation, the method can be used to determine the effective water saturation of a low resistivity hydrocarbon bearing shaly reservoir.
The methodology of the present subject matter uses the SP log, which is substantially equal to the membrane potential log, as contributions from a liquid junction potential and an electrokinetic potential developed across the reservoir can be rendered negligible. A realistic downhole measurement of the membrane potential aids an accurate estimation of the clay conductivity C e. Consequently, an error-free


estimation of the effective water saturation of the low resistivity shaly sand reservoir, which may otherwise be overlooked, may be made.
These and other features, aspects, and advantages of the present subject matter will be better understood with reference to the following description and appended claims. This Summary is provided to introduce a selection of concepts in a simplified form. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. BRIEF DESCRIPTION OF DRAWINGS
The above and other features, aspects, and advantages of the subject matter will be better understood with regard to the following description, appended claims, and accompanying drawings where:
Fig. 1 illustrates a schematic diagram of a well logging system, according to an embodiment of the present subject matter.
Fig. 2 illustrates a cross-sectional view of an earth formation penetrated by a cylindrical bore hole, according to an embodiment of the present subject matter.
Fig. 3 illustrates a spontaneous potential (SP) log recorded against fresh water sand shale depositional sequence of an earth formation.
Fig. 4a illustrates an exemplary method for determining effective water saturation of a hydrocarbon bearing shaly sand reservoir, according to an embodiment of the subject matter.
Fig.4b illustrates an exemplary method for determining initial water saturation of the hydrocarbon bearing shaly sand reservoir of Fig. 4a, according to an embodiment of the subject matter.
Fig. 5 illustrates a chart showing comparative log responses of two nearby wells drilled with low salinity mud and with high salinity mud, respectively, according to an embodiment of the present subject matter.
Fig. 6 illustrates a comparison of a conventional resistivity based technique and the methodology as described in Fig. 4a, according to an embodiment of the present subject matter. DETAILED DESCRIPTION
The subject matter described herein provides a method and a system for determining effective water saturation of a shaly reservoir. The method involves recording of a spontaneous potential (SP) log in a borehole drilled with a saline


drilling mud. The saline drilling mud includes an electrolyte such that the electrolyte renders the contribution of liquid junction potential and electrokinetic potential negligible, thereby only giving the desired membrane potential. The recorded SP log is normalized to compensate for clay volume, which in turn provides realistic estimation of clay conductivity under in-situ conditions. Consequently, substitution of the estimated clay conductivity in the conventional saturation equations provides a substantially accurate measurement of water saturation. For the purposes of explanation, terms "reservoir" and "formation" may be used interchangeably, hereinafter.
Fig. 1 illustrates a schematic diagram of a well logging system 100, according to an embodiment of the present subject matter. The present subject matter also provides a methodology for the evaluation of effective hydrocarbon saturation and water saturation in low resistivity reservoirs, in conjunction with the illustrated well logging system 100.
The well logging system 100 of the present subject matter comprises a logging unit 101, which may be provided in a work vehicle, and a recording unit 102 mounted on top of the logging unit 101. In operation, the logging system 100 can be stationed at a desired drill site and a logging cable 103 from the logging unit 101 can be passed through a groove of a sheave 104. The sheave 104 is rotatably supported on top of a rig structure 105. The rig structure 105 is placed at the drill site such that the logging cable 103 is unwound into a borehole 106. During log data acquisition, logging tools, such as a downhole tool assembly 107 are lowered into the borehole 106. Typically, at a given instant, lowering of the logging tools and data acquisition occurs in a static condition of the borehole 106.
Further, the downhole tool assembly 107 is attached to an end of the logging cable 103 and includes sensors for sensing required logging parameters. The downhole tool assembly 107 can be coupled to the logging unit 101 for processing of the sensed logging parameters. If desired, the logging unit 101 can also be configured to provide a quick estimation of reservoir properties such as water saturation and porosity. However, a detailed processing and interpretation may be carried out separately. The processed logging parameters and processing techniques may be stored in the recording unit 102. A tool centralizer 108 is provided on both fore-ends of the downhole tool assembly 107 to prevent any damage to the downhole tool


assembly 107 and to keep the sensors at a desired stand-off from the wall of the borehole 106.
Typically, when a borehole is drilled with a saline drilling mud having a salinity different from formation water, various potentials such a membrane potential and a liquid junction potential may develop across a formation. For the calculation of the water saturation an accurate estimation of the membrane potential is desired. However, an SP log recorded in the conventional mud system does not provide a realistic estimation of the membrane potential as it contains contributions from liquid junction potential and electrokinetic potential.
In one implementation, the borehole 106 is drilled in the formation 109 and is filled with a saline drilling mud (shown in Fig.2). which is porous and permeable The saline drilling mud includes a mixture of clay, water, salts or electrolytes, polymers, additives, etc. According to an aspect of the present subject matter, the saline drilling mud includes an electrolyte having an anion and a cation with substantially similar mobilities, for example potassium chloride (KC1). Such a drilling mud may be of high salinity and may contain an additive with substantially high viscosity such as partially-hydrolyzed polyacrylamide (PHP A) polymer.
The saline drilling mud advantageously renders the liquid junction potential developed across the formation 109 as negligible. Thus, an SP log recorded in the borehole 106 is substantially equal to the membrane potential developed along the depth of the borehole 106. The saline drilling mud may be interchangeably referred to as the mud, hereinafter. In one implementation, the formation 109 is drilled with the mud having potassium chloride (KCl) as an electrolyte.
In drilling operation, the mud is continuously made to circulate through a drill string including a drill pipe, drill collars, and a drill bit. The mud is made to circulate in an annular space between the borehole 106 and the drill string with the help of a pump (not shown in the figure). However, during the static condition the pump does not circulate the mud in the borehole 106. Further, during the static condition, the downtool assembly 107 may be lowered inside the borehole 106 to sense the required logging parameters. As conventionally known, the mud along with balancing the pore pressure due to the pressure of fluids within the pores of the formation 109 being penetrated, cools and lubricates the drill bit. Further, the mud stabilizes the wall of the borehole 106 and carries drill cuttings to the surface to clear the borehole 106. The density of the mud is so adjusted that the hydrostatic pressure of the mud is more than


the expected pore pressure of the formation 109. The pressure differential between the borehole 106 and the formation 109 forces mud filtrate into the porous and permeable formation 109, a process called invasion. In the invasion process, solid particles of the mud deposit on the walls of the borehole 106 to form a mud cake, whereas the fluid portion or the mud filtrate enters the interstices of the formation 109. The invasion of the mud filtrate continues till the mud cake sufficiently thickens to become impermeable to the invading mud filtrate.
Fig. 2 illustrates a cross sectional view of a formation penetrated by the cylindrical borehole 106. Further, Fig. 2 depicts changes in fluid content and resistivity of various radial segments around the borehole 106.
As aforementioned, the pressure differential from the borehole 106 to the formation 109 forces the mud 202, into the formation 109. As a result of this invasion process, the fluid contents of the formation 109 in the vicinity of the borehole 106 change, and a radial zone is created around the borehole 106. Most of the movable fluids, such as formation water and some hydrocarbons, may be flushed away by the mud filtrate due to invasion. The displacement of the movable fluids leaves an invaded zone 204, also known as flushed zone. The diameter of invasion Di depends upon many factors including formation porosity, formation permeability, and the time elapsed since the formation 109 was drilled. The invaded zone 204 has a bulk resistivity denoted by Rxo and the mud filtrate has a resistivity denoted by Rmf.
Upon formation of the impermeable mud cake, an un-invaded radial zone 206 is created. The un-invaded radial zone 206 is that part of the formation 109 which is not affected by the invasion. The resistivity of the un-invaded zone 206, the formation water, and the mud cake are depicted by Rt, Rw, and Rmc, respectively, in Fig.2. Typically, the resistivity of the invaded zone Rxo, the resistivity of un-invaded zone Rt, and the diameter of invasion Di are obtained in accordance with tool-specific environmental correction charts based upon standard mathematical models and resistivity log measurements with multiple depths of investigations.
In one implementation, the resistivity contrast between the mud filtrate and the fresh formation water in wells drilled with the mud 202 is about 10 to 20 times. For example, the ratios of Rm/ and RH in some wells drilled with the mud 202 in the
Eastern region of India are given in Table 1. Table 1 shows that the resistivity of the mud filtrate is 4-16 times lesser than that of formation water.


Table-1
Mud and formation water resistivity data in wells with KC1 mud as mud 202
(Table Removed)

On comparing the resistivity of a mud filtrate in a conventional low salinity sodium chloride (NaCl)-based mud and in a high salinity KCl-based mud, it was found that the KCl-based mud has about 40 times less resistivity than the conventional NaCl mud.
The salinity of the mud 202 may be higher than the salinities of normally available formation water in fresh water reservoirs formation. In one implementation, the salinity of the mud 202 is higher than 50Kppm, which is substantially higher than

the salinities of normally available formation water in fresh water reservoirs. Further, the pH of the mud 202 may be approximately 7, i.e. substantially neutral.
Fig. 3 illustrates an SP log 300 recorded against a fresh water sand shale depositional sequence of a formation.
Spontaneous potential is a naturally occurring electrical potential difference in a borehole, measured by an electrode relative to a fixed reference electrode. An SP log measures the electric potentials between depths in the borehole and a grounded reference voltage at the surface. Conventionally, SP logs are used for demarcating porous and permeable sand beds from impermeable shale beds.
In one implementation, the SP log 300 is recorded in a borehole such as the borehole 106 with a conventional high salinity mud. The SP log 300 recorded against a fresh water shale sand sequence with the high salinity mud, provides maximum negative potential in shale beds 302-1, 302-2,...302-n, and maximum positive potential in a water bearing sand bed(s) 304. The shale beds 302-1, 302-2,...302-n are hereinafter collectively referred to as shale beds 302. By observing the SP log 300 over a given interval of the formation 109, a shale baseline 306 and a sand baseline 308 can be drawn. The difference of the values at the two baselines 306 and 308 is used to select a cut-off value. The cut-off value is compared with the SP measured at any given depth level of the borehole 106 to determine relative shaliness of the formation such as the formation 109.
The value of SP across the shale beds 302 is almost zero and coincides with the shale baseline 306. A first SP amplitude 309 of water bearing sand bed (s) 304, measured in milli Volts (mV), is almost at its maximum and coincides with the sand baseline 308. The SP log 300 at the hydrocarbon bearing shaly sand zone or bed 310 provides a second SP amplitude 312, which is less than first SP amplitude 309 of the sand bed 304.
The overall maximum deviation from the shale baseline 306 of the water bearing sand bed 304, i.e. the first SP amplitude 309, is composed of two components namely membrane potential Em or Esh depicted as a third SP amplitude 314 and a liquid junction potential Ej depicted as a fourth SP amplitude 316. The high salinity mud environment in the borehole, due to the high salinity mud, provides a positive and high SP amplitude against the shaly sand bed 310, thereby imparting a good sensitivity to changes in the shaliness and hydrocarbon saturation.

The membrane potential is developed in the bore hole due to exchange of positive ions between the high salinity mud and the formation water in underlying/overlying sand bed(s) 304 through the shale beds 302, which are negatively charged. The liquid junction potential is developed due to a difference in the mobility of positive and negative ions undergoing diffusion in the reservoir rock due to salinity difference between the high salinity mud and the formation water. The membrane potential (Em) and the liquid junction potential (Ej) are combined as a series combination of electromotive force's and are thus responsible for the generation of the SP log 300. These two potentials can be mathematically expressed as below.
(Equation Removed)

Where R,T & F are universal gas constant, absolute temperature, and Faraday constant respectively, t_ & t+ are transport numbers for anions and cations, while aw & amf are chemical activities for formation water and mud filtrate respectively.
For field application of the SP log 300, the following more simplified expression can be applied.

(Equation Removed)


Where Rmfe and Rwe are respectively equivalent resistivities of the mud filtrate
and the formation water, and T is the formation temperature in degrees Fahrenheit.
The ratio, will thus determine the sign and amplitude of the SP.

The membrane potential and the liquid junction potential are considered as two potentials connected in series. At a temperature of 75°F:

(Equation Removed)

In addition to the liquid junction potential and the membrane potential, an electrokinetic potential may also be created. The electrokinetic potential, also known as streaming or filtration potential, is caused by filtration of borehole fluids through the mud cake, shale and sometimes low permeability reservoir sections. This potential, however, is generally very small and is regarded negligible. The expression for electrokinetic potential is given by the following expression:
Where ζ, D, P, Rmf & µ are Zeta potential of rock surface in relation to saturating brine, dielectric constant of mud filtrate, pressure differential, resistivity of mud filtrate and viscosity of the mud filtrate respectively. Since ζ, D, Rmf and µ depends upon the salinity of the mud filtrate and the nature of ions, EK depends upon the chemistry of solution.
According to an aspect of the present subject matter, the borehole 106 is drilled with the mud 202 having high salinity value. As discussed previously, the resistivity of the mud 202 is 4 to 16 times lesser than that of the formation water. Further, owing to the high salinity of the mud 202, the resistivity (Rmf) of the mud 202, the zeta potential (ζ) of the reservoir rock surface, and the dielectric constant (D) of the mud 202 are substantially reduced. Additionally, the presence of PHPA polymer used in the mud 202 enhances the viscosity of the mud 202. Therefore, on application of equation (7), the contribution due to the electrokinetic potential comes out to be negligible.
Further, the mud 202 may include KC1 as the electrolyte. The transport number for K+ ions is 0.496 and is approximately equal to that of Cl ions, which is 0.504. The two ions assume the same transport number since both acquire the same electronic configuration as that of Argon atom. In addition to the same transport numbers, both the ions are monovalent in nature, and therefore can carry approximately the same amount of electric current. Thus, when the two KC1 solutions of different salinities, such as a KC1 solution in formation water and a KC1 electrolyte in the mud 202 make an interface, no liquid junction potential is developed.

Moreover, even if the formation water is NaCl-based, very little liquid
+ junction potential is expected due to nearly equal ionic mobilities of K & C1 ions.
The liquid junction potentials for various electrolytes have been theoretically studied
and the value of constant multiplier K for KC1 was found to be 0.1 mV as compared
to 12.7 mV for NaCl, thus the liquid junction potential for the NaCl based mud is 127
times more than that of KC1 based mud such as mud 202.
It is, therefore, evident that the contribution of the liquid junction potential is substantially reduced when the mud 202 is used instead of any conventional mud formulation. The high salinity of the mud 202 does not substantially change the membrane potential as cation transference is unity for a perfect shale membrane irrespective of the electrolyte used. The cation transference is unity when all the anions are blocked by the shale separating the two electrolytes with different salinities. Therefore, the perfect shale membrane will totally block CI" ions whether the KC1 based mud 202 or conventional NaCl based mud is used.
Additionally, a potential called bi-ionic potential is also developed when different salts are present in the mud filtrate and the formation water. However, the bi-ionic potential does not vary significantly with aw/amf ratio, and temperature.
Combining all the sources of SP that constitute an SP log recorded in the mud 202, such as the membrane potential, the liquid junction potential and the bi-ionic potential of the KC1 mud system, the equation for calculating the SP is mentioned as below:

(Equation Removed)
The constant factor of 22 mV in the above equation due to the bi-ionic potential is added throughout the particular logged interval, and therefore does not cause any error in the estimation of the SP along the logged interval.
Moreover, since with depth, the temperature increases and the availability of oxygen in the mud 202 decreases, the chances of development of redox potential are substantially reduced. Further, absence of any oxidizing agents in the mud system also inhibits the development of the redox potential. Hence, the SP recorded, along any logged interval, in the mud 202 is substantially equal to membrane potential along the logged interval.

The high salinity contrast between the mud 202 and the formation water enhances the overall amplitude of the SP log recorded in such a mud environment. The effect of hydrocarbon on the SP log is viewed as if the hydrocarbon bearing layers exhibit more shaliness than their water bearing counterparts with the same amount of clay. Therefore, the SP log recorded in the mud 202 can be used to effectively compensate for the low resistivity in the hydrocarbon bearing shaly sand reservoirs deposited in fresh water environment.
According to an aspect of the present subject matter, the ionic double layer (IDL) attached to clay surfaces, measured quantitatively by cation exchange capacity (CEC) or the electric shale parameter Qv, affect membrane potential of shaly sand reservoirs in the same manner as it affects electrical conductivity. Hence, the SP log recorded in the mud 202 can be considered equivalent to a membrane potential log or a Qv log that contains the effect of clay minerals and their types and the mode of distribution.
In one embodiment, Waxman and Smits model for shaly sand reservoirs, based on the ionic double layer model, is considered. According to the model, following equations (9) and (10) correspond to the water bearing and hydrocarbon bearing shaly sand reservoirs, respectively.
(Equation Removed)

Where Ct is bulk (log measured) conductivity, F is formation resistivity factor, Ce is the clay conductivity term (Ce = B Qv), B is equivalent conductance of clay counter ions, and Qv the cation exchange capacity per unit pore volume. In order to compensate for an increase in conductivity due to presence of clay, the realistic computation of Ce is required.

For clean formations (Ce=0), equations (9) & (11) are reduced to the Archie's equations:

(Equation Removed)
The main electrical parameter of shaly sands used in equation (11) is electric shale parameter Qv. Conventionally, Qv is determined from pulverized core samples in the laboratory through chemical titrations. The main draw back in the implementation of equation (11) with the laboratory measured Qv is the limited data and the destruction of actual geometry of clay distribution. Therefore, a downhole measurement that is directly related to Qv is required to compensate for the loss of resistivity in shaly sand reservoirs.
In one embodiment, a direct relationship of the clay conductivity (Ce) with the membrane potential measurements is established. For the purpose, L.J.M Smits equation for membrane potential developed across shaly sands separating two electrolytes of different salinities is considered. The equation is based upon the concept of transport number and thermodynamical reasoning when ions move under concentration gradient and is illustrated as equation (12).
(Equation Removed)
Where R = Gas Constant, F = Faraday constant and y± are the molal activities of cations and anions, m is molality of the electrolyte, and tNa is Hittorf Transport Number for sodium ions, i.e., cations, in the free electrolyte. tNa is defined as:
(Equation Removed)


Equation (12) implicitly includes the electric shale parameter Qv, since the clay conductivity Ce is electric shale parameter Qv times equivalent conductance of
clay counter ions B. The membrane potential and the electrical conductivity of shaly sands depend on transportation of ions in the electrolyte. Also, membrane potential and the electrical conductivity are affected by surface charges on the clay minerals or shales, thus implying that accurate estimation of the electric shale parameter Qv is important.

The difference of membrane potential and the liquid junction potential is measured in a shaly sand sample by separating two solutions that have m,and m2 molal concentrations and the same is illustrated by the following equation (14).
(Equation Removed)

In perfect shale membranes, the clay conductivity Ce is substantially greater than Cw. Thus, neglecting Cw as compared to Ce, equation (14) for the perfect shale membrane now becomes:
(Equation Removed)

"■I The integrand of equation (14) can be approximated by a rectangular function with height equal to Ce/Cw+Ce and width equal to AUoo , as known in the art. Under this approximation, equation (14) can now be rewritten as follows:
(Equation Removed)
16)
Re-arranging the terms,
(Equation Removed)

The equation (17) establishes a direct relationship of the clay conductivity (Ce) with the membrane potential measurements. Thus, according to an aspect of the present subject matter, the clay conductivity (Ce) itself is estimated in-situ rather than
first computing Qv and multiplying it by empirically derived B, the equivalent conductance of exchangeable cations, to get Ce.
The clay conductivity in hydrocarbon saturated core samples, computed by the equation (17), matches well with the measured values through C 0 -C w measurements at different salinities as studied earlier.

For 100% water saturated zones, substitution of Ce from equation (17) into equation (9) provides the following equation:
(Equation Removed)

Similarly for hydrocarbon bearing zones, the equation can be rewritten as: (Equation Removed)

Where F* & G* are formation resistivity factors for water and hydrocarbon zones respectively and are related through saturation exponent n* as given below:
(Equation Removed)
Substituting G* into equation (19) gives:
(Equation Removed)
Dividing equation (18) by equation (21) gives:
(Equation Removed)

Using I = Co/C, and I* = S~"
(Equation Removed)
Where I and I* are apparent and true resistivity indices of shaly sand. In terms of Sw:
(Equation Removed)

Where [Sw]e is the final true computed water saturation or effective water saturation; Sw is the computed value with multi-mineral model compensated for bulk
volume of clay, but not for hydrocarbon effect; ΔU, is the membrane potential for a perfect shale membrane estimated from SP value in a nearby shale that has good hole condition and maximum clay; ΔUsw is the clay corrected SP at depth; and ΔUsw=1 is

clay corrected SP against water bearing shaly sand. Conventionally, equation (24) is not used for in-situ estimation of effective water saturation since ΔUsw is computed by core analysis.
However, according to an aspect of the present subject matter, an SP log recorded in the mud 202 aids for in-situ estimation of ΔUsw and the effective water saturation. The only dependent parameter in equation (24), is shaly sand saturation exponent n*, which may be measured from core samples.
Fig.4a illustrates an exemplary methodology 400 by way of a flow chart elucidating the methodology or the technique employed for determining effective water saturation of a hydrocarbon bearing shaly sand reservoir, according to an embodiment of the subject matter. In one implementation, the methodology 400 is used for determining effective water saturation of a low resistivity hydrocarbon bearing shaly sand reservoir.
At step 402, an initial estimation of water saturation of a reservoir under investigation is made. The initial estimation of water saturation refers to estimation of the water saturation using conventional techniques and methodology. The same is explained in detail with respect to Fig.4b.
At step 404, an SP log, recorded in a saline drilling mud, is used for in-situ estimation of membrane potential. The recorded SP log is substantially equal to a membrane potential log as contribution to the SP due to liquid junction potential and electrokinetic potential is rendered negligible. In one implementation, the SP log is recorded in a borehole,such as the borehole 106, drilled with the mud 202. Since, the mud 202 contains an electrolyte that includes a cation and an anion with substantially similar mobilities, the contribution of the liquid junction potential is made negligiable.
At step 406, the recorded SP log is normalized. In one implementation, the SP log is normalized for clay volume using the shale volume model. Further, the membrane potential of a perfect shale membrane and a 100% water bearing reservoir can be calculated from the SP log and/or related equations such as equation (8). The normalized SP log can be used for determining the clay conductivity Ce in-situ.
Subsequent to normalization of the SP log, at step 408, an effective water saturation is calculated. In one implementation, the effective water saturation is calculated using the estimated values of the membrane potential for the perfect shale membrane, clay corrected membrane potential for a 100% water bearing reservoir,

clay corrected membrane potential at a depth from the normalized SP log, and the initial water saturation estimated using the shale volume model. The effective water saturation thus calculated is used to measure hydrocarbon saturation, as known in the art.
The estimation of the effective water saturation may also be dependent on the shaly sand saturation exponent n* measured from core analysis. In one implementation, the effective water saturation is calculated from a saturation equation such as equation (24). The effective water saturation thus computed compensates for the reduction in resistivity, due to enhanced electric shale factor Qv, by realistic estimation of membrane potential..
Therefore, the present methodology 400 compensates for the volumetric effect of the clay minerals, the type and distribution of the clay minerals, the chemical environment of the reservoir, and accounts for the hydrocarbon effect. Further, the methodology 400 estimates the effective water saturation based on known and in-situ measured physical quantities and not from estimated empirical constants. The empirical constants that have been used in the technique are core derived a, m, and n, which are also used in the Archie's equation for clean formations. Thus, the methodology 400 provides a realistic estimation of the water saturation for a low resistivity hydrocarbon bearing reservoir.
Further, the methodology 400 accounts for the effect of fine grained nature of the rock. This is due to the use of the membrane potential log (SP log) to compensate for the reduction in the resistivity depending upon the electric shale parameter Qv, which is a measure of total charge in a double layer irrespective of the phenomenon responsible for its generation.
Fig.4b illustrates an exemplary methodology 402 by way of a flow chart elucidating the methodology or the technique employed for determining the initial water saturation of the shaly sand reservoir, according to an embodiment of the subject matter. In one implementation, to compute the initial water saturation, a mineralogical model based on sedimentological or petrographical studies on core samples is developed. Typically, the core samples are studied for lithology and are tested for the presence of various minerals. Based on the minerals found in the samples, a mineralogical model is developed as illustrated at step 430.
Subsequent to development of the mineralogical model, at step 432 petro-physical parameters such as porosity, permeability, grain density, and Archie's

parameters including constant "a", cementation factor "m", saturation exponent "n", are determined. The petro-physical parameters may be calculated from petro-physical laboratory studies on the core samples.
At step 434, processing parameters for the minerals or mineral assemblages present in the mineralogical model are determined. The processing parameters may include density, sonic travel time, and photoelectric factor. An initial estimation of processing parameters is made from standard databases for pure minerals such as quartz, calcite, and pyrite and/or form the cross plots of various lithological indicator logs for mineralogical assemblages such as rock fragments, chloritized mica and wet mixed layer clays. The lithological indicator logs may include a GR log, a neutron-density log, a sonic velocity log, etc. The quantitative knowledge of the lithological constituents present in a well as a function of depth is considered to be valuable in assessing aspects of exploration, evaluation, and production of hydrocarbons.
Further, at step 436 processing parameters for the hydrocarbons and the formation water are determined. The processing parameters for the hydrocarbons may be determined from the conventional pressure volume temperature (PVT) analysis of field samples.
At step 438, available log data is processed to achieve minimum incoherence between the actual log data recorded in the reservoir and the available log data constructed using aforementioned processing parameters for the minerals, hydrocarbons and formation water. The available log data may be processed by a multi-mineral inverse modelling technique or any conventional error minimization technique using the developed mineralogical model and estimated parameters. The inverse modelling technique is used to estimate quantities that are directly or indirectly related to the measured quantity.
In one implementation, upon processing of the available log data, various formation parameters, such as effective porosity and water saturation of the un-invaded zone are calculated and the same is illustrated at step 440. The calculated water saturation is taken as the initial water saturation. The initial water saturation may be calculated using the shale volume model based saturation equations, such as Indonesian equation, without using the SP and GR logs.
The computation of the initial water saturation using the shale volume model accounts for the bulk or volumetric nature of the clay minerals present. However, the shale volume model does not compensate for the hydrocarbon effect, the chemical

environment, the distribution of clay minerals, and the type of clay minerals present in the reservoir. Additionally, any other model that solves the similar purpose, i.e., accounts for the volumetric effect of the clay minerals, may also be used. Depending on the preferences of a user, at step 442, the computed and the estimated quantities, i.e., mineral content, grain density, and porosity, may be validated with the core studies.
In another implementation, the methodology 400 can be used for effective water saturation of a high resistivity or a normal resistivity hydrocarbon bearing shaly sand reservoir. For the purpose, adequate resistivity contrast may be developed between the formation water and the mud filtrate to achieve an SP log sufficiently sensitive to changes in shaliness and hydrocarbon saturation.
The methodology 400 provided in the present invention addresses the effect of total shale content of a reservoir rock (laminated, dispersed and structural). Further, the methodology 400 implicitly incorporates the effect of rock conductivity, which is due to the shale or clay minerals and also because of other fine grained minerals like silts and granular micas and even micas with altered surfaces (rough surfaces). The effect of clays and other fine grained minerals on bulk rock conductivity is estimated from in-situ measurement of membrane potential and is incorporated in the conductivity based saturation equation. Hence, the method 400 automatically takes care of the internal structure and physical and chemical properties of the reservoir rocks and fluids and their interrelationship.
The order in which the methodologies 400 and 402 are described is not intended to be construed as a limitation, and the steps described can be combined in other ways obvious to a person skilled in the art. Additionally, individual blocks may be added or deleted from the method without departing from the spirit and scope of the subject matter described.
Fig. 5 illustrates comparative log responses against a first well 501 and a second well 502, according to an embodiment of the present subject matter. In one implementation, the first well 501 and the second well 502 considered for the study are 7 metres apart. The two wells 501 and 502 being substantially close to each other have substantially similar reservoir properties. The first well 501 is an exploratory well drilled with conventional low salinity NaCl based drilling mud and the second well 502 is drilled with a high salinity KCl-based mud such as the mud 202. In one implementation, the methodology or the interpretation technique 400 is applied for the

quantitative evaluation of the second well 502, which is a fresh water shaly silty sandstone reservoir. The methodology 400 is then compared with the results of those obtained by a conventional resistivity based technique in the second well 502 as explained in detail with respect to Fig.6.
A first resistivity log 504-1 of the first well 501 and a second resistivity log 504-2 of the second well 502 illustrate that the resistivity contrast between the hydrocarbon and the water bearing sections is low. The two resistivity logs 504-1 and 504-2 provide in-situ measurements of the resistivity of an uninvaded zone. The two resistivity logs 504-1 and 504-2 show that the resistivity contrast between the hydrocarbon bearing zones in the interval 2493-2499 meters in the second well 502 and in the interval 2497-2504 meters in the first well 501 is the lowest.
Further, a first GR log 506-1 of the first well 501 and a second GR log 506-2 of the second well 502 are illustrated. An increase in the second GR log 506-2 due to the mud 202 in the second well 502 as compared to the first GR log 506-1 is also depicted.
It can be seen that in sand section, a first density log 508-1 of the first well 501 and a second density log 508-2 of the second well 502 read almost same. Likewise, a first neutron log 510-1 of the first well 501 and a second neutron log 510-2 of the second well 502 also read same.
A first SP log 512-1 in the first well 501 drilled with the conventional NaCl drilling mud responds basically to lithology variations whereas a second SP log 512-2 of the second well 502 responds to lithology changes as well as to the changes in formation fluids. In the second well 502, at 2505 metres to the top of sand (2489 meters), a reduction in spontaneous potential can be seen from the second SP log 512-2, which indicates an oil water contact (OWC) at 2005 meters.
Further, in the second well 502 and at an interval between 2494-2500 metres, the trend observed in the second SP log 512-2 and the second resistivity log 504-2 is substantially the same. The observation suggests that the second SP log 512-2 and the second resistivity log 504-2are affected by the CEC and the electric shale parameter Qv in the same manner. Hence, the second SP log 512-2 can be used for applying correction to the second resistivity log 504-2.
Fig 6 illustrates a comparison of interpretation results of the log data of the second well 502 processed using the methodology and the technique 400 of the present subject matter and a conventional resistivity technique 602. A normalized SP

log 603 is illustrated for the calculation of effective water saturation using the methodology 400.
According to methodology 400 and conventional resistivity technique 602, based upon the core studies, a four mineral model consisting of clay, feldspar Lithic fragments, mica, and sand was used for mineral volume and porosity computation. The mineralogical model was validated by percentage wise matching of computed volumes with those reported in the core studies against the interval 2507-2516 meters. Additionally, the computed porosity and grain density were validated against the petro-physical studies in the core interval of 2499-2508 meters of the nearby first well 501.
The production of water free hydrocarbons from the interval 2489-2500 meters with average hydrocarbon saturation of 40%-50% and pay thickness 13 meters, computed using the methodology 400 is validated by the actual hydrocarbon production in the well 502. Further, an OWC 604 is observed at 2005 meters. The average hydrocarbon saturation and the pay thickness computed in the second well 502 using the conventional resistivity technique 602 are 30% and 3.5 meters respectively. The pay thickness 13 m with methodology 400 and 3.5 m with methodology 602 are estimated using water saturation cut-off of 70%. This means that hydrocarbon pay is defined where S w, water saturation, is less than or equal to
70%. Further, the hydrocarbon saturation computed by the methodology 400 in the second well 502 against the interval 2494-2500 meters, which exhibits lowest resistivity, is 40%-50% as compared to 10%-20% computed by the conventional technique 602 in the same second well 502. The accurate estimation of the membrane potential by the SP log 512-2 recorded in the well 502 drilled with mud 202 along with the methodology 400 provides an accurate estimation of the hydrocarbon saturation in the well 502.
The previously described versions of the subject matter and its equivalent thereof have many advantages, including those which are described below. The present subject matter provides a methodology 400 for substantially precise estimation of water saturation, and hence hydrocarbon saturation of low resistivity shaly sand reservoirs having fresh formation water. The methodology 400 using the SP log integrated with conventional saturation equations provides error-free

estimation of water saturation and/or hydrocarbon saturation content than only resistivity based methods.
Additionally, the present invention provides a cost effective method that is based upon conventional log measurements and does not require high-end technology tools such as nuclear magnetic resonance (NMR), full-bore formation micro-imager (FMI), and multi-component induction resistivity, etc.
While certain features of the claimed subject matter have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will now occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes that fall within the true spirit of the claimed subject matter.

I/We claim:
1. A method comprising:
determining an initial water saturation of a shaly reservoir;
recording in-situ a spontaneous potential in a borehole having saline drilling mud, wherein said saline drilling mud comprises an electrolyte such that the spontaneous potential recorded along said borehole is substantially equal to a membrane potential along said borehole;
normalizing said spontaneous potential to compensate for clay volume; and
computing an effective water saturation using said normalized spontaneous potential and said initial water saturation.
2. The method as claimed in claim 1, wherein said electrolyte comprises anions and cations with substantially similar mobilities.
3. The method as claimed in claim 1, wherein said computing an effective water saturation comprises estimating a shaly sand saturation exponent (n*), and wherein said computing is based on an ionic double layer model.
4. The method as claimed in claim 1, wherein said determining an initial water saturation is based on a shale volume model.
5. A well logging system (100) comprising:
a saline drilling mud (202), wherein said saline drilling mud (202) includes an electrolyte comprising an anion and a cation with substantially similar mobilities;
a downhole tool assembly (107) suspended in a borehole (106), wherein said borehole (106) is drilled with said saline drilling mud (202); and wherein said downhole tool assembly (107) comprises at least one sensor to sense at least one logging parameter; and
a logging unit (101) communicatively coupled to said downhole tool assembly (107), wherein said logging unit (101) processes said sensed logging parameter.

6. The system as claimed in claim 5, wherein said logging parameter is a spontaneous potential along said borehole (106), and wherein said spontaneous potential is substantially equal to membrane potential along said borehole (106).
7. The system as claimed in claim 5, wherein said borehole (106) is drilled in a low resistivity hydrocarbon bearing shaly sand reservoir.

8. The system as claimed in claim 5, wherein said electrolyte is potassium chloride (KC1).
9. The system as claimed in claim 5, wherein said saline drilling mud (202) comprises an additive having substantially high viscosity.
10. The system as claimed in claim 9, wherein said additive is partially-hydrolyzed polyacrylamide (PHP A).
11. The system as claimed in claim 5, wherein said saline drilling mud (202) has a pH value of about 7.
12. The system as claimed in claim 5, wherein said saline drilling mud (202) has salinity of about 50Kppm.