![Location of Illizi Basin in eastern province of Algeria. The studied TFT field has been marked by circle [17], modified.](https://www.researchgate.net/profile/Reda-Laouini/publication/390524820/figure/fig1/AS:11431281397059885@1745504779234/Location-of-Illizi-Basin-in-eastern-province-of-Algeria-The-studied-TFT-field-has-been_Q320.jpg)
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Citation: Laouini, R.; Hacini, M.;
Merabti, H.; Medjani, F.; Mahmoud, O.
Mud Loss Analysis Through
Predictive Modeling of Pore Pressure
and Fracture Gradients in Tin Fouye
Tabankort Field, Western Illizi Basin,
Algeria. Energies 2025,18, 1836.
https://doi.org/10.3390/
en18071836
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licenses/by/4.0/).
Article
Mud Loss Analysis Through Predictive Modeling of Pore
Pressure and Fracture Gradients in Tin Fouye Tabankort Field,
Western Illizi Basin, Algeria
Reda Laouini 1, Messaoud Hacini 1, Hocine Merabti 2,3, Fethi Medjani 1and Omar Mahmoud 4, *
1Laboratory of Geology of the Sahara, Kasdi Merbah University, Ouargla 30000, Algeria;
redageo89@gmail.com (R.L.); hacini.messaoud@univ-ouargla.dz (M.H.); medjanifethi21@gmail.com (F.M.)
2LabSTIC Laboratory, Guelma 24000, Algeria; merabti.hocine@univ-ouargla.dz
3Department of Drilling and Oil Field Mechanics, Faculty of Hydrocarbons, Kasdi Merbah University,
Ouargla 30000, Algeria
4Department of Petroleum Engineering, Faculty of Engineering and Technology, Future University in Egypt
(FUE), Cairo 11835, Egypt
*Correspondence: omar.saad@fue.edu.eg
Abstract: This study examines the distribution of pore pressure (PP) and fracture gradient
(FG) within intervals of lost circulation encountered during drilling operations in the
Ordovician reservoir (IV-3 unit) of the Tin Fouye Tabankort (TFT) field, located in the Illizi
Basin, Algeria. The research further aims to determine an optimized drilling mud weight
to mitigate mud losses and enhance overall operational efficiency. PP and FG models
for the Ordovician reservoir were developed based on data collected from five vertical
development wells. The analysis incorporated multiple datasets, including well logs,
mud logging reports, downhole measurements, and Leak-Off Tests (LOTs). The findings
revealed an average overburden gradient of 1.03 psi/ft for the TFT field. The generated
pore pressure and fracture gradient (PPFG) models indicated a sub-normal pressure regime
in the Ordovician sandstone IV-3 reservoir, with PP values ranging from 5.61 to 6.24 ppg
and FG values between 7.40 and 9.14 ppg. The analysis identified reservoir depletion due
to prolonged hydrocarbon production as the primary factor contributing to the reduction in
fracture gradient, which significantly narrowed the mud weight window and increased the
likelihood of lost circulation. Further examination of pump on/off cycles over time, coupled
with shallow and deep resistivity variations with depth, confirmed that the observed mud
losses were predominantly associated with induced fractures resulting from the application
of excessive mud weight during drilling operations. Based on the established PP and FG
profiles, a narrow mud weight window of 6.24–7.40 ppg was recommended to ensure the
safe and efficient drilling of future wells in the TFT field and support the sustainability of
drilling operations in the context of a depleted reservoir.
Keywords: pore pressure; fracture gradient; lost circulation; reservoir depletion; mud
window
1. Introduction
Wellbore instability poses a significant challenge in drilling operations [
1
,
2
]. The exca-
vation process alters the in situ stress field surrounding the borehole, leading to potential
failure of the formation [
3
]. The stress state at any given depth is characterized by a verti-
cal stress component, primarily governed by overburden pressure (OVP) and horizontal
principal stresses influenced by tectonic forces and pore fluid pressure [
4
]. Maintaining
Energies 2025,18, 1836 https://doi.org/10.3390/en18071836
Energies 2025,18, 1836 2 of 19
wellbore stability requires establishing an equilibrium between the in situ stress field and
the applied wellbore pressure. Control of the wellbore pressure via the drilling mud is
therefore crucial for ensuring both formation integrity and operational safety.
The mud window represents a critical paradigm in petroleum engineering, delineating
the operational parameters essential for maintaining wellbore integrity during drilling
processes. This analytical construct is fundamentally predicated on two fundamental geo-
logical parameters: pore pressure (PP) and fracture gradient (FG), which collectively define
the permissible range of drilling fluid weight [
5
]. Mismanagement of the mud window
not only risks operational safety but also significantly contributes to non-productive time
(NPT), which has become a key performance metric in the oil and gas industry. For example,
Dodson et al. [
6
] reported that 24 % of NPT in the Gulf of Mexico’s shelf gas wells was
associated with challenges such as shallow gas flows, kicks, and mud losses. Such incidents
not only delay operations but also lead to increased operational costs, environmental risks,
and potential abandonment of wells.
PP, a fundamental geomechanical property, quantifies the intrinsic fluid pressure
within rock formation pore spaces [
7
]. Conversely, fracture gradient represents the maxi-
mum pressure threshold at which the surrounding rock matrix experiences structural fail-
ure [
8
]. The interplay between these two parameters defines the mud window—a narrow
operational corridor that drilling engineers must meticulously manage to prevent potential
geological catastrophes such as formation collapse or uncontrolled fluid migration.
Pioneering research by Eaton [
9
] first systematized the conceptual understanding of PP
prediction, establishing foundational methodologies for interpreting subsurface pressure
dynamics. Subsequent investigations by Mouchet and Mitchell [
10
] further elaborated on
the critical relationship between PP and wellbore stability, highlighting the potential catas-
trophic consequences of inadequate pressure assessment. Furthermore, empirical studies
by Teufel et al. [
11
] and more recent research by Kassem et al. [
12
] have demonstrated the
increasing complexity of mud window management in depleted reservoir systems. These
investigations underscore the dynamic nature of in situ stress regimes and their profound
implications for drilling fluid weight optimization.
PP and FG modeling play a critical role in optimizing well design, mitigating drilling
risks, and ensuring formation stability, particularly in depleted reservoirs. Several recent
studies have demonstrated the effectiveness of PP-FG models in these settings. For instance,
Ghosal et al. [
13
] developed a comprehensive simulation for carbon capture and storage
(CCS) applications, integrating fracture gradient and pore pressure predictions to enhance
the stability of depleted reservoirs in Southeast Asia. Similarly, Hashemi and Kovscek [
14
]
employed coupled flow–geomechanics modeling to analyze pore pressure gradients and
stress alterations following reservoir depletion, specifically focusing on depleted reservoirs
in the Gulf of Mexico. Beyond predictive modeling, field-specific investigations have
provided insights into real-time wellbore stability challenges. Kuakool et al. [
15
] developed
pre-drill 1D geomechanical models for optimizing drilling programs in Thailand’s Phitsan-
ulok Basin, where deviations in pressure trends were observed in depleted sand intervals,
highlighting the need for localized pore pressure calibration. Meanwhile, Melikov et al. [
16
]
introduced an innovative approach for real-time pore pressure prediction during drilling
operations in the offshore “White Tiger” Oilfield, incorporating continuous modeling ad-
justments to mitigate instability risks. Although significant advancements have been made
in predictive PP and FG modeling, many studies primarily focus on theoretical simulations
and fail to incorporate real-time analyses of mud loss incidents occurring during active
drilling in hydrocarbon reservoirs. The present study builds upon previous research by
investigating actual mud loss events in the Tin Fouye Tabankort (TFT) field, located in
the northwestern part of the Illizi Basin, Algeria. This field has experienced persistent
Energies 2025,18, 1836 3 of 19
challenges related to mud losses, particularly during the drilling of vertical development
wells targeting the Ordovician sandstone reservoir (IV-3 unit). By integrating empirical
field data with geomechanical modeling, this research provides a more comprehensive
understanding of wellbore instability mechanisms and their implications for drilling op-
erations in this reservoir. The primary objectives include quantifying the distributions
of PP and fracture gradient across the intervals of observed mud losses, identifying the
causal mechanisms, and proposing an optimized mud weight window calibrated to the
current reservoir conditions. This optimized window is intended to facilitate safer and
more efficient drilling operations, minimizing risks and ensuring operational continuity for
future wells.
2. Materials and Methods
2.1. Description of Study Area
The Illizi Basin, located in the eastern province of Algeria, spans an area of approxi-
mately 108,424 km² and has been a focal point for petroleum exploration since 1956 [
17
].
It belongs to a series of cratonic basins in the Algerian Sahara that are situated along the
northern edges of the Precambrian Reguibat and Hoggar massifs. Structurally, the basin is
bound by the Amguid Ridge to the west, the Tihemboka Ridge to the east [
18
], the Berkine
(Ghadames) Basin to the north, and the Hoggar Massif to the south
(Figure 1) [19].
Hydro-
carbon generation in the Illizi Basin occurred primarily during the Middle to Late Jurassic
and Early Tertiary periods [
20
]. Structural traps within the basin were predominantly
formed during Mesozoic and Tertiary deformation events, driven by vertical movements
of the Precambrian basement [
21
]. These features, combined with the basin’s favorable
geological conditions, have established it as a significant site for hydrocarbon exploration
and production.
The TFT field, situated in the north-western part of the Illizi Basin, approximately 360
km SSE of the Hassi Messaoud field, is a mature oil- and gas-producing area. The field’s gas
cap was first discovered in 1961, followed by the identification of oil in 1965. Production
commenced in 1967 [
17
]. The primary reservoir in the field is the Ordovician sandstone,
which is characterized by two distinct units: IV-3 and IV-2 (Figure 2). These units consist of
periglacial sediments, with the IV-3 unit serving as the main reservoir due to its uniform
petrophysical properties and consistent thickness. In contrast, the IV-2 unit exhibits poorer
reservoir quality and significant variability in thickness [17].
Figure 1. Location of Illizi Basin in eastern province of Algeria. The studied TFT field has been
marked by circle [17], modified.
Energies 2025,18, 1836 4 of 19
Figure 2. TFT field Lithostratigraphy, unpublished Sonatrach internal report, 2020, modified.
2.2. Data Source
The dataset analyzed in this study comprises five vertical development wells drilled in
the Ordovician reservoir of the TFT field. Four of these wells (TF2, TF3, TF4, and TF5) were
drilled recently (2022–2023) and encountered lost circulation while the 6 in. hole section
was being drilled. In contrast, the fifth well (TF1) was drilled earlier, in the year 2000. All
wells were specifically designed to target hydrocarbon production from the Ordovician
sandstone reservoir (IV-3 Unit), which has a variable thickness ranging between 11 and
25 m (Table 1).
A comprehensive dataset comprising logging measurements and operational records
was employed to analyze the reservoir’s geomechanical characteristics and address chal-
lenges related to lost circulation. The dataset included gamma-ray logs, density logs, and
sonic slowness measurements for both compressional and shear waves, offering critical
insights into lithology, formation density, and elastic properties. These parameters were
pivotal in estimating PP and FG distributions. In addition to logging data, operational
records such as mudlogging reports, drilling reports, Leak-Off Tests (LOTs), and Repeat
Formation Tests (RFTs) were integrated to enhance the precision of the geomechanical
analysis. Gamma-ray logs provided a reliable means of lithological differentiation, while
density logs were instrumental in calculating OVP—a key component in stress distribution
Energies 2025,18, 1836 5 of 19
models [
22
]. Sonic slowness measurements enabled the determination of Poisson’s ratio, a
crucial elastic property that plays a central role in modeling the mechanical behavior of the
formation under varying stress conditions [23].
Table 1. Tops of Ordovician reservoir units in the studied wells. In Wells TF2 and TF5, the top of
III-3 unit has not been penetrated by drilling (data collected from internal unpublished report of
Sonatrach Company).
Wells
Ordovician
Unit TF1 TF2 TF3 TF4 TF5
IV-3 Unit 2001 2057 2003 2000 1979
Top IV-2 Unit 2014 2073 2014 2025 2000
(m) III-3 Unit 2066 - 2070 2056 -
TD 2130 2128 2150 2120 2120
2.3. Procedure
2.3.1. Estimation of Poisson’s Ratio
The mechanical properties of rock significantly influence wellbore stability [
24
–
26
].
These properties are typically categorized into two groups: rock strength parameters and
elastic properties, the latter including Poisson’s ratio [
27
]. In this study, Poisson’s ratio (v)
is estimated using the following Equation [28]:
v=Vp2−2Vs2
2(Vp2−Vs2)(1)
where
Vp
and
Vs
represent the compressional and shear wave velocities, respectively, in
units of meters per second.
The static Poisson’s ratio is conventionally determined through laboratory testing on
core samples; however, due to the unavailability of core data in this study, an alternative
approach was adopted. Specifically, the dynamic Poisson’s ratio, derived from sonic log
measurements, was utilized as an approximation of the static Poisson’s ratio, following
methodologies established in previous research [
19
,
29
]. To ensure the validity and reliability
of this assumption for geomechanical characterization, the estimated dynamic Poisson’s
ratio was compared with static values reported in prior studies conducted within the same
region [30].
2.3.2. Estimation of OVP
OVP, also known as vertical stress (Sv), is the pressure exerted on a subsurface forma-
tion by the cumulative weight of overlying sediments and pore fluids [
19
]. This parameter
is fundamental to geomechanical analysis, serving as the principal vertical stress compo-
nent in stress distribution models. It is particularly critical for the accurate determination of
PP and FG distributions, which are essential for ensuring wellbore stability and optimizing
drilling operations. OVP can be estimated using bulk density log data, as described by
Plumb et al. [31], through the following formula:
OVP =ZH
0ρ(H)g dH (2)
where
OVP
is the vertical stress,
ρ(H)
is the the bulk density of the overlying sediments
and fluids (varies with depth), and grepresents the gravitational acceleration.
Accurate data analysis is essential for all studied wells to ensure reliable geomechan-
ical assessments. Due to the absence of bulk density logs from the surface, the Amoco
Energies 2025,18, 1836 6 of 19
equation was utilized to generate pseudo-density profiles for the missing sections. This
approach is widely recognized and has been employed in numerous studies [
19
,
32
,
33
].
After the pseudo-density was calculated, it was integrated with the existing bulk density
log data to produce a composite density profile, which was then used to estimate the OVP.
In the study conducted by Radwan et al. [
33
], the default Amoco fitting parameters for
vertical stress were modified to better align with the geological characteristics of the study
area. Specifically, they adjusted the mudline density to 2.15 g/cm³ and the Amoco exponent
to 0.85. In the present study, the default values (1.95 g/cm³ for mudline density and 0.6
for the Amoco exponent) did not match the observed wireline density trends. Through
iterative testing and calibration using data from Wells TF3 and TF4, optimal values of
2.25 g/cm³ for shallow density and 0.9 for the Amoco exponent were identified. These
adjusted parameters were subsequently applied across all studied wells to enhance the
accuracy of the density profile. Figure 3illustrates the discrepancies between the default
Amoco fitting parameters and the modified values derived for Wells TF3 and TF4, high-
lighting the improved alignment with observed density trends achieved through parameter
refinement. Figures 3a,b show the composite density profiles (Track 04) for calculating over-
burden pressure (Track 05) in Wells TF3 and TF4, respectively. Track 02 represents Amoco
density using default fitting parameters (1.95 and 0.6), and Track 03 is the Amoco density
using modified fitting parameters (2.25 and 0.9), which follows the wireline density (red)
trend better.
(a)
(b)
Figure 3. Discrepancies between the default Amoco fitting parameters and the modified values
derived for Wells TF3 and TF4: (a) Composite density profile (Track 04) for calculating overburden
pressure (Track 05) in TF3. (b) Composite density profile (Track 04) for calculating overburden
pressure (Track 05) in TF4.
Energies 2025,18, 1836 7 of 19
2.3.3. Estimation of PP
PP refers to the pressure exerted by fluids within the pore spaces of a geological
formation. It plays a pivotal role in ensuring primary well control during drilling operations
by balancing formation PP with the hydrostatic pressure of the drilling fluid [
34
]. Effective
well control is maintained within two critical boundaries: the maximum PP and the
minimum fracture pressure. Maintaining this balance is essential for avoiding wellbore
instability, influxes, or blowouts [
35
]). In this study, PP gradients were estimated using
compressional sonic slowness logs. Normal compaction trends (NCTs) were established
within shale zones to serve as a baseline for the analysis. Subsequently, the sonic Eaton
equation was applied to derive PP gradients, as expressed below [36]:
PP =OBG −(OBG −Ph)∗DTn
DT 3
(3)
where
Ph
is the hydrostatic pressure (0.433 psi/ft), and
OBG
is the overburden gradi-
ent.
DTn is
the compressional sonic log response against shale along NCT.
DT
is the
compressional sonic slowness log.
Shale zones were identified using gamma-ray logs, supported by lithological infor-
mation from mudlogging cuttings as recorded in the master log [
37
]. These shale intervals
were critical for defining the NCT and ensuring the accuracy of the PP estimations.
2.3.4. Estimation of FG
Accurately determining the FG, which represents the minimum horizontal stress, is
essential for wellbore stability and fracture design [
38
]. Methods such as LOTs, mini/micro-
fracture tests, and hydraulic fracture analysis provide direct and precise measurements of
this parameter [
39
]. In this study, two established methodologies were utilized to estimate
the FG: The first method, developed by Eaton and Eaton, calculates the FG using the
following Equation [28]:
FGeaton =v
1−v(OBG −PP) + PP (4)
Eaton’s method facilitates the incorporation of lithological variations [
40
], such as
shale and sandstone, into FG estimations by accounting for the influence of Poisson’s ratio,
which is derived from Equation
(3)
. According to Zhang and Wieseneck [
41
], this approach
is particularly suitable for older geological formations, including Cretaceous-aged and pre-
Cretaceous formations. In these cases, Eaton’s method remains applicable when Poisson’s
ratios are computed using sonic log data, allowing for more accurate fracture gradient
predictions in deep, complex reservoirs.
The second method, employed in Well TF1, estimates the FG using the effective
stress ratio as proposed by Matthews and Kelly [
42
]. The FG is estimated using the
following equation:
FGmk =PP +K(OBG −PP)(5)
where Kis the effective stress ratio, a parameter derived from LOT measurement.
RFT and LOT measurements were conducted in the Ordovician reservoir for Well TF1
to provide calibration for PP and FG estimates derived from indirect methods. However, in
Wells TF2, TF3, TF4, and TF5, the execution of these measurements was precluded by the
occurrence of lost circulation within the Ordovician IV-3 unit. This loss event significantly
constrained the ability to obtain direct data, thereby limiting the calibration and validation
of geomechanical parameters in these wells.
Energies 2025,18, 1836 8 of 19
Sonic log-based methods, such as Eaton’s approach, are widely employed for PP
prediction. However, these methods are inherently subject to limitations that can introduce
uncertainties in estimated PP values. Several factors beyond effective stress, including the
presence of organic matter, free hydrocarbons, and diagenetic alterations, can significantly
influence sonic velocity responses, leading to discrepancies in PP estimations [
43
]. Ad-
ditionally, unconsolidated sediments and heterogeneous lithologies may distort velocity
readings, further reducing the accuracy of sonic log-based models [
44
]. In this study, a
comparative analysis was conducted by correlating calculated values with measured mud
weights. This approach has been previously employed in other research as a means to
complement sonic velocity measurements and minimize prediction errors [19].
3. Results
3.1. Poisson’s Ratio and OVP
The results of this study demonstrate that Poisson’s ratio for the Ordovician sandstone
reservoir ranges from 0.055 to 0.18 (Table 2), indicating limited lateral deformation relative
to axial stress. Conversely, Poisson’s ratio for shales exhibits values between 0.20 and
0.29, indicative of their higher ductility and enhanced capacity for lateral deformation
under axial loading. These observations agree with the findings of English et al. [
30
], who
performed uniaxial and triaxial mechanical tests on core samples from the southern Illizi
Basin, confirming the contrasting mechanical responses of sandstone and shale formations.
OVP was estimated using composite density logs from the five analyzed wells.
The calculations revealed an average OBG of 1.036 psi/ft at a depth of approximately
2130 m ± 15 m.
For instance, in Well TF1, the OVP was determined to be 7205 psi at a depth
of 2132 m, corresponding to a gradient of 1.03 psi/ft. The consistent OBG values observed
across all wells suggest that the vertical stress regime in the studied field has remained
stable over time, despite the effects of prolonged hydrocarbon production.
Table 2. Estimation of Poisson’s ratio in the studied wells.
Poisson’s
Ratio
Formation Lithology Well
TF1 TF2 TF3 TF4 TF5
IV-3 Sandstone 0.10–0.13 0.06–0.14 0.05–0.19 0.04–0.15 0.06–0.18
Shale 0.14–0.20 / / / /
IV-2 Sandstone 0.12–0.14 0.06–0.18 / 0.08–0.19 0.09–0.18
Shale 0.18–0.29 0.15–0.23 0.14–0.27 0.18–0.29 0.17–0.28
III-3 Shale 0.16–0.29 / 0.18–0.28 0.19–0.26 /
3.2. PP and FG Modeling
3.2.1. Well TF1
The development of PPFG model for Well TF1 was conducted to characterize the
geomechanical properties of the Ordovician IV-3 unit (Figure 4). The pore pressure was
estimated using sonic log data, calibrated against direct pressure measurements obtained
from RFT over the interval 2001–2014 m. The PP exhibited a gradient of 0.422 psi/ft,
corresponding to an average pressure of 2784 psi (8.13 ppg). This value is slightly below
the hydrostatic pressure typically used during drilling operations. The fracture pressure
was determined to have a gradient ranging between 0.53 and 0.60 psi/ft (10.19–11.53 ppg),
equating to approximately 3705 psi. This estimate was calibrated using LOT data obtained
at a depth of 1999 m. The obtained FG was compared with the findings of Baylocq et
Energies 2025,18, 1836 9 of 19
al. [
45
], which documented fracture gradient values ranging from 0.54 to 1.06 psi/ft in
the region. The higher gradient values observed in wells located in the southern part of
the field were attributed to tectonic effects. Operational reports from the rig indicate that
the 6 in. section was drilled using oil-based mud (OBM) with a density ranging between
8.18 and 8.22 ppg. This mud weight proved to be a reliable proxy, maintaining a slightly
overbalanced condition without exceeding the FG. Notably, no instances of mud loss were
reported in the daily drilling records, confirming the effectiveness of the selected mud
weight in maintaining wellbore stability and avoiding circulation losses.
3.2.2. Well TF2
During the 6 in. drilling phase, operations encountered the Silurian Argillaceous
Gothlandian formation, along with the Ordovician IV-3 and IV-2 units. Upon drilling
through the cement, the operators proceeded with OBM at a density of 7.76 ppg, cover-
ing the interval from 2050 m to 2059 m. At this depth, lost circulation occurred within
the Ordovician IV-3 unit. Despite multiple attempts to seal the loss zone by injecting
lost circulation material (LCM) pills, these efforts proved ineffective. The operators
faced substantial delays in resuming drilling, necessitating tripping operations, reduc-
ing the mud weight to 7.59 ppg, and circulating at variable flow rates until mud returns
were re-established.
Analysis of the generated PPFG model for Well TF2 (Figure 4) indicated that the
current PP and FG for the Ordovician IV-3 unit were calculated at 5.81 ppg and within
the range of 7.40 to 8.27 ppg, respectively. The initial drilling fluid density of 7.76 ppg
(equivalent circulating density (ECD) = 7.92 ppg; flow rate = 1250 L/min) was subsequently
reduced to 7.59 ppg (ECD = 7.74 ppg; flow rate = 1250 L/min). However, both mud
weights exceeded the FG at certain intervals, resulting in bottom hole pressure surpassing
the fracture threshold and triggering lost circulation. When the flow rate was reduced to
800 L/min, the ECD decreased, subsequently minimizing the loss rate. Drilling continued
under conditions of partial fluid loss.
3.2.3. Well TF3
Prior to initiating the drilling of the new 6 in. section, the existing mud with a density
of 9.01 ppg was replaced by a lighter mud of 7.76 ppg. Drilling commenced at a depth
of 2002 m following the removal of the cement. However, at 2006 m, lost circulation
was encountered. In response, LCM pills with concentrations ranging from 300 kg/m³ to
800 kg/m³, were pumped into the wellbore, but these efforts were unsuccessful in fully
mitigating the losses. A reduction in the mud weight to 7.59 ppg, coupled with a decrease
in the flow rate from 1250 L/min to 500 L/min, eventually led to a noticeable decline in
the loss rate. Analysis of the PPFG model for Well TF3 revealed that in the Ordovician
reservoir (IV-3 unit), the mud weight applied during drilling, ranging between 7.76 ppg
and 7.43 ppg (ECD between 7.93 ppg and 7.59 ppg at flow rates of 1250–800 L/min),
exceeded the FG profile, which varied between 7.56 ppg and 8.78 ppg at certain intervals
(Figure 4). This overpressure condition contributed to the occurrence of lost circulation.
Upon further reducing the flow rate to 500 L/min, the ECD dropped below the fracture
pressure threshold, effectively halting the losses and stabilizing the wellbore.
Energies 2025,18, 1836 10 of 19
Figure 4. Interpreted PP, OVP, and FG profiles of the studied wells in the TFT field.
3.2.4. Well TF4
The operational sequence for this well proceeded as follows: The initial drilling mud
with a density of 9.01 ppg was displaced by a lower-density mud of 7.76 ppg. Cement was
drilled out over the interval from 1995 m to 2000 m, marking the initiation of formation
drilling at 2000 m. Mud losses were observed at depths of 2003 m, 2007 m, and 2016 m,
corresponding to the top of the Ordovician IV-3 unit. In response, LCM pills with concen-
trations ranging between 600 kg/m³ and 1400 kg/m³ were introduced into the wellbore;
however, these mitigation efforts were ineffective in halting fluid losses. A reduction in
flow rate, coupled with a decrease in mud weight to 7.43 ppg, successfully curtailed the
losses. Drilling operations continued under controlled flow conditions to mitigate the risk
of partial mud losses and maintain wellbore stability. The PPFG model developed for Well
TF4 revealed that, under static conditions, the applied mud weight in the range of 7.43 to
7.76 ppg surpassed the fracture gradient, which varied between 7.67 and 9.14 ppg across
certain intervals of the Ordovician sandstone IV-3 unit (Figure 4). This discrepancy suggests
that during dynamic drilling conditions, ECD exceeded the FG, further exacerbating the
potential for fluid losses. The occurrence of lost circulation is attributed to the utiliza-
tion of a drilling mud window that was not adequately aligned with the present state of
the reservoir.
Energies 2025,18, 1836 11 of 19
3.2.5. Well TF5
Following the displacement of the drilling mud from 9.01 ppg to 7.51 ppg and the
removal of cement between 1968 m and 1972 m, formation drilling commenced at a depth of
1972 m. Mud losses were encountered at 1979 m, corresponding to the top of the Ordovician
sandstone reservoir (IV-3 unit). Similar to other wells, LCM pills were deployed, and the
mud weight was further reduced to 7.35 ppg to facilitate the continuation of drilling
operations. As illustrated in Figure 4, the PPFG model reveals that the mud weight profile
closely overlaps the FG profile across a significant interval. This overlap indicates that the
ECD exceeded the fracture gradient, causing mud losses.
4. Discussion
A comparative analysis with the earlier drilled well (TF1), where no mud losses were
reported, revealed a consistent pattern of mud losses in the other four studied wells (TF2,
TF3, TF4, and TF5). Examination of the generated PP and FG profiles indicated that the
mud weight applied during drilling exceeded the FG in multiple intervals, resulting in
lost circulation within the Ordovician sandstone reservoir (IV-3 unit). Detailed analysis of
the estimated parameters (Table 3) showed an average depletion in reservoir pressure of
744 psi (
∆
PP = 5.13 MPa), accompanied by a reduction in fracture pressure of approximately
855 psi (∆FP = 5.896 MPa).
Table 3. Estimated pore pressure and fracture gradients in the Ordovician reservoir. The last column
shows the ECD used while drilling.
Well Formation Pore Pressure (PP) Fracture Gradient (FG) Drilling Mud
Weight
psi/ft ppg psi/ft ppg ppg
TF1
IV-3 0.422 8.11 0.531–0.60 10.32–11.53
IV-2 0.453 8.71 0.53–0.68 10.19–13.07 8.178–8.512
III-3 0.451 8.67 0.56–0.69 10.76–13.26
TF2 IV-3 0.303 5.81 0.385–0.430 7.40–8.27 7.598–7.765
IV-2 0.31–0.44 5.96–8.46 0.400–0.610 7.69–11.73
TF3
IV-3 0.325 6.24 0.393–0.456 7.56–8.78
IV-2 0.38 7.30 0.430–0.630 8.27–12.11 7.431–7.765
III-3 0.38 7.30 0.450–0.700 8.65–3.46
TF4
IV-3 0.315 6.06 0.398–0.475 7.67–9.14
IV-2 0.425 8.17 0.480–0.680 9.23–13.07 7.431–7.765
III-3 0.40 7.69 0.520–0.590 10.00–11.34
TF5 IV-3 0.292 5.61 0.387–0.439 7.45–8.44 7.348–7.515
IV-2 0.41–0.44 7.88–8.46 0.45–0.67 8.65–12.88
The hydrocarbon production from the Ordovician reservoir in the TFT field com-
menced in 1967 [
46
], with peak production achieved in 1976 at a rate of approximately
122.05 thousand barrels per day (bpd) of crude oil and condensate (Figure 5). Current
economic projections estimate that production will continue until the field reaches its
economic limit in 2059. However, this prolonged extraction has resulted in the depletion of
this reservoir, which has notably impacted wellbore stability during drilling operations.
Reservoir depletion has led to alterations in the in situ stress magnitudes and the mud
weight window, narrowing the operational range available for drilling. These changes
have increased the risk of exceeding the FG, thereby contributing to mud losses and as-
sociated operational challenges. The findings underscore the critical need for adaptive
Energies 2025,18, 1836 12 of 19
drilling strategies, including the reassessment of mud weight parameters, to account for
the evolving geomechanical conditions of the reservoir.
Figure 5. Production evolution of crude oil in the TFT field.
Mud Losses Monitoring While Drilling
Lost circulation can be classified into natural and induced losses, each governed by
distinct mechanisms. Natural losses occur through pores or matrix in high-permeability
formations, such as coarse sands, gravels, and depleted reservoirs, where mud losses are
common when pore sizes exceed the mud particle size by a factor of three [
47
]. Permeable
natural fractures, with apertures ranging from microns to several millimeters, also con-
tribute significantly to circulation losses due to their ability to facilitate fluid migration [
47
].
Additionally, cavernous formations, formed over geological timescales in soluble rocks
like limestone, dolomite, and salt, create voids of varying sizes, from microscopic to large
tunnels, resulting in severe mud losses. Induced losses, on the other hand, occur when the
ECD exceeds the formation’s FG, causing the formation to fracture. These losses are often
linked to pressure surges during drilling, leading to the opening of induced fractures and
subsequent fluid loss. The most commonly utilized method for detecting mud losses during
drilling involves monitoring changes in the level of the mud pits. Figure 6qualitatively
illustrates the response of mud losses over time, as reflected by variations in mud pit levels.
The temporal behavior of pit level changes differs depending on the type of formation
loss: pores, natural fractures, or induced fractures. Losses into porous formations typically
begin slowly and increase gradually over time, as the fluid permeates the pore spaces.
In contrast, losses into natural fractures exhibit a distinct pattern, characterized by an
initial rapid loss followed by a gradual decline as the fractures reach equilibrium with the
fluid pressure [
48
,
49
]. For drilling-induced fractures, the behavior is more complex and
highly sensitive to changes in fluid pressure. Fracture apertures respond dynamically to
variations in pressure, leading to alternating loss or gain of drilling fluid. For instance,
turning the pumps off and on during drilling can result in frequent pressure fluctuations,
causing induced fractures to alternately open and close [
50
]. This dynamic process directly
influences the flow behavior, with intermittent fluid losses or gains depending on the
pressure differential across the fracture plane.
The same approach is used in this study; pit-level monitoring is combined with mud
flow dynamics to evaluate fluid losses during drilling operations. The distinctive signatures
observed in the combined dataset enabled discrimination between losses attributed to pre-
existing fractures and those associated with hydraulically induced fractures formed during
Energies 2025,18, 1836 13 of 19
the drilling process. In this context, Figure 7presents a comprehensive analysis of the
evolution of drilling parameters in Well TF3, integrating pit-level monitoring with mud
flow dynamics to systematically assess fluid loss behavior within the study area.
Figure 6. Type of loss zone from pit-level trace [50].
Energies 2025,18, 1836 14 of 19
Figure 7. Pump on/off signature during mud losses in induced fractures in Well TF3.
The analysis of Figure 7is divided into five distinct sequences, highlighting the mud
losses dynamics during drilling operations. Sequence 1 corresponds to the drilling of the 6
in. hole section within the IV-3 unit, during which partial mud losses were observed at a
rate exceeding 1 m³/h. To mitigate these losses, mud transfer operations were undertaken,
reducing the mud weight and consequently lowering the loss rate (Sequence 2). In Sequence
3, the mud pumps were switched off during pipe connection operations, resulting in a
stabilized mud level with a slight increase attributed to backflow. This behavior reflects
the reduction in dynamic pressure when the pumps are off, allowing the induced fractures
to partially close under the natural formation stress. The observed slight increase in mud
level suggests that the losses are pressure-dependent, a characteristic commonly associated
with hydraulically induced fractures. Sequence 4 involved a stepwise reduction in the
mud flow rate to 1300 L/min and subsequently to 800 L/min. This adjustment led to a
significant decrease in the mud loss rate, demonstrating a direct correlation between flow
rate and loss mitigation. In Sequence 5, further reduction in the flow rate to 500 L/min
resulted in the cessation of mud losses and a slight rise in the mud pit level. This response
strongly supports the hypothesis of induced fractures, as their closure is highly sensitive to
pressure changes. At a flow rate of 500 L/min, the pressure dropped below the fracture
closure pressure, enabling partial or full closure of the induced fractures. The observed
sensitivity of mud losses to flow rate changes provides compelling evidence that the losses
are attributable to induced fractures rather than natural fractures.
A comparative analysis of Figures 6and 7reveals that the overall slope of Sequence
1 exhibits a pattern that closely aligns with the characteristic curve of seepage losses.
However, a more detailed analysis of the period between 00:00 and 02:05, which falls
within this sequence, suggests that the observed pit-level decrease during this timeframe
was primarily attributed to normal drilling operations rather than seepage losses. As
drilling progressed, the drilling mud was continuously displaced to fill the newly formed
wellbore, while additional mud volume was lost with the cuttings removed at the shale
shakers. Furthermore, surface equipment, including the mud cleaner and centrifuge, also
contributed to surface-level mud reductions. These combined factors account for the
gradual pit-level decline, indicating that the reduction was a result of routine drilling
processes rather than seepage-related losses.
Energies 2025,18, 1836 15 of 19
Another method utilized to validate the hypothesis of induced fractures involves the
utilization of real-time Logging-While-Drilling (LWD) measurements. This approach is
particularly effective in distinguishing naturally occurring fractures from those induced
during drilling operations by analyzing the separation of shallow and deep resistivity
measurement curves over time [
51
]. Such analysis facilitates the identification of fracture
characteristics and allows for targeted adjustments to the drilling program, thereby mit-
igating the effects of induced fractures on wellbore stability and enhancing operational
efficiency. In this study, real-time resistivity data acquired from Well TF3 was evalu-
ated to investigate fracture behavior and the formation’s response to drilling operations.
Figure 8illustrates
a distinct divergence between shallow and deep resistivity measure-
ments in the interval between 2006 and 2013 m, which correlates with the reported mud loss
events. This observation provides further evidence of the relationship between elevated
shallow resistivity and the presence of induced fractures within these zones. The resistivity
analysis conclusively indicates that the observed mud losses in the studied intervals are
predominantly caused by induced fractures. The anomalies in shallow resistivity, charac-
terized by abrupt increases and significant variability, are indicative of OBM infiltrating the
fractures. These findings, supported by gamma-ray data and corroborating observations,
strongly suggest that the fractures were induced during drilling operations because of mud
pressures exceeding the formation’s fracture resistance.
Figure 8. Shallow resistivity, deep resistivity, and gamma rays while drilling in mud loss zones in
Ordovician reservoir IV-3 unit (Well TF3).
To mitigate mud losses resulting from induced fractures, various drilling strategies can
be implemented to enhance wellbore stability. Wellbore strengthening techniques, such as
the application of optimized lost circulation materials (LCMs), play a crucial role in sealing
fractures and preventing further fluid losses. Additionally, mud weight optimization is es-
sential to ensure that wellbore pressure remains within the safe operating window, thereby
minimizing the risk of fracture propagation. Furthermore, Managed Pressure Drilling
(MPD) provides a real-time pressure control mechanism, allowing for precise adjustments
to bottom-hole pressure and reducing the impact on fractured formations. When inte-
grated with real-time monitoring technologies, these mitigation strategies can significantly
minimize mud losses and improve wellbore stability, particularly in depleted reservoirs.
Energies 2025,18, 1836 16 of 19
5. Conclusions
This study provided a comprehensive analysis of PP, OVP, and FG within the Ordovi-
cian sandstone reservoir of the TFT field, with the objective of identifying the primary
factors contributing to mud losses experienced during drilling operation. Prolonged hydro-
carbon production has led to significant depletion of the reservoir, resulting in a notable
reduction in pore pressure from 2784 psi to 2041 psi, which, in turn, has caused a corre-
sponding decrease in the fracture gradient from 3705 psi to 2850 psi. This narrowing of
the pressure window, driven by depletion-induced stress redistribution, has increased the
risk of lost circulation and wellbore instability during drilling operations. To mitigate these
challenges, a drilling mud weight window of 6.24 to 7.40 ppg is recommended, reflecting
the estimated boundaries of pore pressure and fracture gradient in the Ordovician IV-3
reservoir. Adopting the optimized mud weight window significantly improves wellbore
stability, thereby minimizing the risk of lost circulation and the associated operational
costs. By effectively reducing mud losses, this approach decreases the reliance on addi-
tional drilling fluids and lost circulation materials (LCMs), resulting in direct cost savings.
Furthermore, maintaining an optimal mud weight mitigates wellbore instability, reducing
non-productive time (NPT) caused by well control incidents and remedial interventions.
Precise mud weight selection enhances drilling efficiency, lowers operational expenditures,
and ultimately improves the economic viability of the project. Future research could ex-
pand on this analysis by conducting a comprehensive cost–benefit evaluation to quantify
these advantages in similar depleted reservoirs, providing valuable insights for reservoir
management and drilling optimization strategies.
The findings underscore the critical need for adaptive drilling strategies that account
for evolving reservoir conditions, highlighting the importance of continuous monitoring
and adjustment of mud weight to ensure operational efficiency. However, the study also
revealed certain limitations that constrained the depth of the analysis, most notably the
unavailability of image log data, which hindered the ability to conduct a more thorough
geomechanical assessment. The absence of such data limited the accurate identification
of fracture orientation, the characterization of in situ stress fields, and the determination
of mechanical properties within the reservoir rock—key factors necessary for a holistic
understanding of subsurface conditions and fracture mechanics. Future investigations
should prioritize the acquisition and integration of borehole image logs into geomechanical
modeling to enhance the accuracy of fracture width distribution and fracture initiation
pressure (FIP) estimation, both of which are critical for wellbore strengthening and the
optimization of lost circulation material (LCM) design. These logs provide high-resolution
visualizations of fracture geometry, orientation, and density, allowing for a more precise
assessment of formation behavior under stress conditions. Accurate fracture width distri-
bution is essential for the effective selection and design of LCMs, ensuring that the particle
size distribution (PSD) of the materials aligns with fracture aperture dimensions, thereby
improving fracture sealing efficiency and mitigating fluid losses.
Additionally, further geomechanical studies are recommended to evaluate in situ
stress magnitudes and directions, characterize the mechanical properties of loss-prone
intervals, and analyze stress path evolution to better understand the subsurface stress state
and the effects of reservoir depletion. Such studies will provide valuable insights into the
mechanisms governing mud losses and fracture propagation, enabling the design of more
effective drilling programs and contributing to the long-term sustainability of petroleum
production in the region. By addressing current data gaps and advancing the understanding
of reservoir geomechanics, operators can enhance drilling efficiency, minimize operational
risks, and extend the productive lifespan of mature reservoirs, ensuring the continued
viability of hydrocarbon extraction in the TFT field.
Energies 2025,18, 1836 17 of 19
Author Contributions: Conceptualization, R.L., M.H., H.M., F.M. and O.M.; methodology, R.L., M.H.,
H.M. and F.M.; software, R.L., H.M. and F.M.; validation, R.L., H.M., F.M. and O.M.; formal analysis,
M.H., H.M., F.M. and O.M.; investigation, R.L. and F.M.; resources, R.L. and F.M.; writing—original
draft preparation, R.L. and F.M.; writing—review and editing, R.L., H.M., F.M. and O.M. visualization,
H.M., F.M. and O.M.; supervision, O.M.; project administration, F.M. and O.M.; funding acquisition,
R.L., F.M. and O.M. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Data Availability Statement: All data will be available from the corresponding author upon request.
Acknowledgments: The authors would like to express their sincere gratitude to Sonatrach and
especially to the personnel of the Production Division, Base Irara, Hassi Messaoud, for their invaluable
help in the preparation of this scientific paper.
Conflicts of Interest: The authors declare that there are no conflicts of interest regarding the publica-
tion of this manuscript.
Abbreviations
The following abbreviations are used in this manuscript:
ECD Equivalent circulating density
FG Fracture gradient
LCM Lost circulation material
LOT Leak-Off Test
LWD Logging While Drilling
NCT Normal compaction trends
NPT Non-productive time
OBG Overburden gradient
OBM Oil-based mud
OVP Overburden pressure
PP Pore pressure
PPFG Pore pressure fracture gradient model
RFT Repeat Formation Test
Sv Vertical stress
TFT Tin Fouye Tabankort
TVD True vertical depth
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