A multi-proxy approach to detect the pore pressure and the origin of overpressure in sedimentary basins: An example from the Gulf of Suez rift basin

Abstract

The pore pressure gradient and fracture gradient (PPFG) are critical parameters for drilling mud weight design in the energy industry. Successful drilling operations can be achieved successfully through the understanding of the pore pressure and fracture pressure in the subsurface succession. The scope of this research is to use an integrated approach that encompasses well-logging, basin modeling, drilling-based interpretations, and reservoir measurement methods to gain a reasonable PPFG model and decrease the drilling uncertainties in the El Morgan oil field in the Gulf of Suez. Moreover, it investigates the overpressure generation mechanisms in the basin, which have not been studied before in this area. In this work, PPFGs of more than 16 km of cumulative thick sedimentary succession were modeled and evaluated using an integrated approach. This study utilizes Eaton’s sonic and resistivity-based methods for pore pressure evaluation, while vertical stress was calculated based on the composite density profile. The study revealed that the top geo-pressure was detected at a depth of 1,030 m of Tortonian sediments. Late Miocene sediments reveal hard over-pressure with a maximum gradient of 0.55 PSI/feet, while Middle Miocene sediments exhibit mildly over-pressured, normal, and sub-normal pore pressure zones. The lowest pore pressure values were measured in the Langhian-Serravalian Kareem reservoir with a gradient of 0.29 PSI/feet. With the exception of a slight difference in the reservoir section, the pore pressure profiles in the northern and southern parts of the El Morgan oil field are relatively similar. Reservoir connectivity is believed to be the main reason behind pore pressure magnitude differentiation in the Middle Miocene reservoirs. The key mechanism for generating overpressure has been identified as disequilibrium compaction, and reservoir overcharging may contribute as an excess-pressure generation mechanism at the reservoir level. The presented approach can be applied in PPFG studies for both development and exploratory geomechanical studies in other areas of the Gulf of Suez basin or elsewhere in the world.

Introduction

Abnormal pore pressure is one of the main challenges for drilling engineers and exploration geologists, and it can be sub-classified into overpressure and sub-normal pressure (Figure 1) (e.g., Bourgoyne et al., 1986; Mouchet and Mitchele, 1989; Neuzil, 1995; Yassir and Bell, 1996; Osborne and Swarbrick, 1997; Sayers et al., 2002; Ramdhan and Goulty, 2010; Ramdhan and Goulty, 2011; Zhang, 2011; Radwan et al., 2019a; Radwan et al., 2020a; Radwan, 2021b). Overpressure generation mechanisms (Figure 2) have been studied in many sedimentary basins, and they are linked with disequilibrium compaction (e.g., Martinsen, 1994; Hart et al., 1995; Klaus, 1999; Vejbæk, 2008; Kumar and Rao, 2012; Marín-Moreno et al., 2013; Wang et al., 2016; Drews et al., 2019; Zhang et al., 2019; Li et al., 2021), clay diagenesis (e.g., Jeans, 1994; Lahann et al., 2001; Katahara, 2006; Lahann and Swarbrick, 2011), tectonic activities (e.g., Hao et al., 2004; Luo et al., 2007), hydrocarbon generation (Spencer, 1987; Osborne and Swarbrick, 1997; Hansom and Lee, 2005; Chi et al., 2010), and thermal effects (e.g., Mello and Karner, 1996; He et al., 2002).

FIGURE 1

FIGURE 2

Historically and despite decades of research into the subsurface sediment characteristics, it remains difficult to predict critical reservoir parameters of strata buried in sedimentary basins such as pore pressure (e.g., Gretener, 1979; Audet and McConnell, 1992; Martinsen, 1994; Gordon and Flemings, 1998; Dutta, 2002; Chopra and Huffman, 2006; Gutierrez et al., 2006; Zhang, 2011; Radwan et al., 2019b; Baouche et al., 2020a; Radwan et al., 2020a; Baouche et al., 2020b; Ganguli and Sen, 2020; Radwan and Sen, 2021a; Radwan, 2021b; Radwan and Sen, 2021b) and fracture pressure (e.g., Anderson et al., 1973; Traugott, 1997; Draou and Osisanya, 2000; Radwan et al., 2019b; Sen and Ganguli, 2019; Tariq et al., 2019; Radwan et al., 2020a; Radwan, 2021b). The importance of pore pressure and fracture pressure is related to their influence on drilling operations (e.g., Gray-Stephens et al., 1994; Swarbrick, 2012; Sen et al., 2020; Abdelghany et al., 2021; Radwan, 2021b), exploration (e.g., O’connor et al., 2011a; John et al., 2014), and reservoir stability and production (e.g., Hillis, 2000; Agbasi et al., 2021; Radwan and Sen, 2021a; Radwan and Sen, 2021b; Kassem et al., 2021).

In the oil and gas industry, pore pressure is measured in reservoirs using specific tools (i.e., bottom-hole pressure gauge, well testing), and it can be predicted or estimated using indirect methods (Radwan et al., 2019b). Pore pressure can be measured in permeable zones (e.g., Swarbrick, 2002; Dasgupta et al., 2016; Sen et al., 2017; Adouani et al., 2019; Radwan et al., 2019b; Dasgupta et al., 2019; Radwan et al., 2020a; Radwan, 2021b). On the other hand, seismic velocities (e.g., Sayers et al., 2002; Chopra and Huffman, 2006; Bachrach et al., 2007; Khan et al., 2017; Hussain and Ahmed, 2018), well logs (e.g., Zhang, 2011; Wessling et al., 2013; Radwan et al., 2019b) and basin modeling (e.g., Nordgård Bolås et al., 2004; Radwan et al., 2020a; Li et al., 2022) are used to predict and estimate pore pressure in frontier sedimentary basins. Drilling parameters and well logs can be used for pressure estimation while drilling (e.g., Mouchet and Mitchele, 1989; Zhang, 2011; Peters et al., 2017; Bourgoyne et al., 1991; Alam et al., 2019). Standard methods, including effective-depth methods and empirical methods (e.g., Eatons’ method, Bowers’ method), have been used for pore pressure prediction in the industry. However, these methods have been used with fair success in areas like the Gulf of Mexico, where sedimentation rates are fairly rapid. Applying these methods in other areas, e.g., the North Sea and the Gulf of Suez, has been more problematic due to the differences in the used parameters and geological conditions (Law and Spencer, 1998; Helset et al., 2009; Shaker, 2015; Snee, 2015; Radwan et al., 2019b; Radwan, 2021b). However, many researchers rely solely on one method for interpreting pore pressures, which may not be efficient in some areas. Recently, researchers have applied machine learning to predict pore pressure in sedimentary basins (e.g., Ahmed et al., 2019; Jafarizadeh et al., 2022; Radwan et al., 2022), as well as 3D modeling being used in pore pressure modeling (e.g., Lopez et al., 2004; Altmann et al., 2014; Radwan, 2022a; Chen et al., 2022).

Reviewing the previous literature on pore pressure prediction and detection methods suggests that geophysical logging has been used for pore pressure prediction in many basins globally (e.g., Eaton, 1975; Traugott, 1997; Bowers, 2001). Reservoir measurements have been used for PPFG model calibration and as direct measurement methods (e.g., Drews et al., 2018; Radwan, 2018; Sen et al., 2019, Sen et al., 2020; Radwan, 2021b). Also, drilling events can be utilized to calibrate the pore pressure model (e.g., Zhang, 2011; Brahma et al., 2013; Das and Chatterjee, 2018a; Das and Chatterjee, 2018b; Radwan et al., 2019b; Mahetaji et al., 2019; Radwan et al., 2020a). In addition, basin modeling has been considered as the primary tool for pressure prediction in frontier areas. Basin modeling results can give a clear image of sedimentation rate, tectonics, erosion, etc., which consequently affect the geopressure mechanism (e.g., Thomsen, 1998; Darby et al., 1998; Bjørlykke et al., 2010; Karlsen and Skeie, 2006; Couzens-Schultz and Azbel, 2014; Snee, 2015; Satti, et al., 2015; Burgreen-Chan et al., 2015; Peters et al., 2017; Mosca et al., 2018; Nagy et al., 2019; Radwan et al., 2020a). However, there is no preferred method that could guarantee and be commonly accepted as better than another method. Therefore, the capability of integrating most of the previously mentioned methods can provide a higher degree of confidence for the predicted pore pressure fracture gradient (PPFG) model.

The Gulf of Suez basin is classified as one of the challenging basins in terms of drilling due to complex tectonic and structural settings (Radwan, 2018; Abass et al., 2019; Radwan et al., 2019b; Radwan et al., 2020a; Radwan, 2021b). However, to date, overpressure generation mechanisms have not been studied before in the Gulf of Suez basin, despite their importance and implications for drilling activity. In this work, the proposed approach relies on the integration of more than one method to obtain the most appropriate PPFG model for the studied basin area of El Morgan field. Basin modeling, reservoir, and drilling data were used as additional inputs with geophysical logging for pore pressure prediction and calibration in the studied oil field. The integration of the previously mentioned tools can drive exemplary modeling of the geopressure. Also, overpressure generation mechanisms in the Gulf of Suez basin were investigated in this work, which have not been studied before and may have implications for the overpressure prediction process, and consequently achieving successful drilling in the studied area. The prime objectives of this work are to: 1) detect the overpressure generation mechanism in the El Morgan area that has not been investigated before in the rift basin, 2) present an improved integrated workflow approach that can act as a valuable reference case in sedimentary basins using combined methods, 3) extend our knowledge of the pore pressure distribution in the penetrated formations of the studied area, and 4) highlight the pore pressure regimes and geopressure zones within the entire (Middle Miocene to recent) sequence.

Geologic setting and lithostratigraphy

The Gulf of Suez rift basin (Figure 3) is an iconic offshore basin that formed in the Oligocene-Miocene period, and lies in the northwest branch of the Red Sea. As evidenced by geophysical and borehole data, the basin is filled with more than a 5-km-thick sedimentary sequence ranging from the Precambrian to the Quaternary (Metwalli et al., 1981; Metwalli et al., 1982; El-Hattab, 1982; Montenat et al., 1988; EGPC, 1996; Radwan, 2022b), which is punctuated by several unconformities of different magnitudes and ages (Figure 3). The studied area of El Morgan oil field is situated in the south central offshore area of the rift basin, where numerous hydrocarbon plays are present (Figure 3) (Alsharhan and Salah, 1995; EGPC, 1996; Bosworth and McClay, 2001; Barakat et al., 2002; Youssef et al., 2002; Alsharhan, 2003; Radwan, 2014; Attia et al., 2015; Abudeif et al., 2016a; El Ayouty, 2017; Abudeif et al., 2018; Radwan, 2018; Radwan et al., 2019a; Radwan et al., 2019b; Radwan et al., 2019c; Radwan et al., 2020a; Radwan et al., 2020b; Radwan et al., 2020c; Radwan et al., 2021a; Radwan et al., 2021b; Radwan et al., 2021c; Radwan et al., 2021d; Radwan et al., 2021e; Ali et al., 2022). El Morgan field is located on the southwest coast of the Sinai Peninsula, covering an area of roughly 46 km² (Bentley and Biller, 1990; Radwan, 2014; Attia et al., 2015). El Morgan field is classified as the biggest giant oil field in Egypt with more than 1.5 BBO reserves. The stratigraphic sequence of El Morgan oil field is classified into three main depositional mega sequences, namely pre-rift, syn-rift, and post-rift (Brown, 1980; Attia et al., 2015; Abudeif et al., 2016a; Abudeif et al., 2016b; Radwan et al., 2019b; Radwan et al., 2019c; Radwan, 2021a; Radwan et al., 2021a; Radwan, 2021b; Radwan et al., 2021b; Radwan, 2021c; Radwan et al., 2021c; Radwan et al., 2021d; Radwan et al., 2021e). The deposition of sediments in the study area took place in different depositional environments (EGPC, 1996). Two main sandstone reservoirs were deposited during the syn-rift time. The Kareem Formation and Belayim Formation (Hammam Faraun Member) (Figure 4) are typical of a fan delta depositional environment (El-Ashry, 1972; EGPC, 1996; Hughes et al., 1997). Miocene sandstone rocks are the main reservoir rocks, and they trap hydrocarbons that originate from the organic-rich carbonate (Campanian-Maastrichtian and Eocene), shales (Paleocene), and marls (Miocene) (Brown, 1980; Rohrback, 1982; Barakat et al., 1997; AlSharahan, 2003; El Nady, 2006; El Diasty and Peters, 2014). The thick evaporites of the Miocene section are the sealing rocks in the area (AlSharahan, 2003; Radwan, 2014; Radwan et al., 2021c).

FIGURE 3

FIGURE 4

The tectonic evolution of this area is linked to the tilted fault block system in the rift basin (Robson, 1971; Patton et al., 1994; Schutz, 1994; Bosworth et al., 1998; Radwan et al., 2020b; Moustafa and Khalil, 2020). The field structure is a NW-SE trending, anticlinal, horst block, with dips of <6–8° (Figure 5) (Gawad et al., 1986; Khalil and Meshrif, 1988; Rashed, 1990; EGPC, 1996; Alsharhan, 2003; Jackson et al., 2006; Ali et al., 2016; Radwan, 2018; Radwan et al., 2019b; Radwan et al., 2021c). The El Morgan oil field is divided into the north and south portions by the El Morgan hinge zone (Figure 5). The studied A well is located in the northern part of the field, while the H well is located in the southern part of the field, as shown in Figure 5.

FIGURE 5

Materials and methods

The data of eight offshore wells that represent the northern and southern parts of the El Morgan field were used in the execution of this work. The studied wells are named (A, B, C, D, E, F, G, and H). Wells A and B were used for modeling, while other wells’ data were used as offset wells (Figure 5). All available data, including a high-resolution geophysical log suite consisting of gamma, resistivity, formation bulk density, and sonic logs, were the key inputs for this study.

Vertical stress and pore pressure

The weight of the overburden rock is called vertical stress (σV) or overburden (Plumb et al., 1991; Shaker, 2007; Paul et al., 2009; Zhang 2011). The composite density profile (Eq. 1) was utilized for overburden stress calculations in the region using available data (Radwan et al., 2020a; Radwan, 2021b). Finite data in the topmost part of the surface section in the studied wells was considered a severe challenge in this study. The Amoco density method was utilized to count the pseudodensity in the surface section (Eq. 2) (Paul et al., 2009; Radwan et al., 2019b). The estimated density from the Amoco equation was appended to the wireline density logs, and hence the composite density profile was developed for the studied wells (Plumb et al., 1991; Matthews, 2004; Radwan et al., 2019b).

The vertical stress gradient (OBG) calculation applying the Amoco method can be expressed by Eq. 1:

The hydrostatic pressure in the area of the Gulf of Suez is equivalent to 8.7 (pounds per gallon) (Selim et al., 2003; Selim and Badawy, 2010; Radwan, 2018; Radwan et al., 2019b; Radwan et al., 2020a; Radwan, 2021b). The identification of shale zones in this study is based on well logs and lithology descriptions. The normal compaction trend (NCT) was considered as the hydrostatic pressure which is equivalent to 8.7 (pounds per gallon) (Radwan, 2018; Radwan et al., 2019b; Radwan et al., 2020a). Eaton’s sonic and resistivity methods were used to estimate the pore pressure from the eight wells (Eqs 3, 4) (Eaton, 1975).

Fracture pressure

The fracture pressure was determined using the Eaton fracture method (Eaton, 1975). The fracture pressure was calibrated with the formation integrity test (FIT) data from the studied wells to check the fracture pressure profile. The previously used Poisson’s ratio in the Gulf of Suez was used in this study (Selim et al., 2003; Selim and Badawy, 2010; Radwan et al., 2019b; Radwan et al., 2020a; Radwan et al., 2020b). The fracture pressure equation is expressed as the following:

Burial history modeling and drilling events

1D basin modeling has been created for the sedimentary section of the studied field using Schlumberger’s PetroMod^© (V. 2018). The bottom hole temperature was estimated from 1D basin modeling and validated by the actual measured temperature in the wells using the Horner method (Kutasov and Eppelbaum, 2005). The stratigraphic section used in building the basin model is based on the biostratigraphic and lithostratigraphic approaches in the area of El Morgan Field, which has thick Miocene sediments (Radwan, 2021b). Furthermore, internal biostratigraphic and geological lithostratigraphic reports from the literature were used to build the representative history model (Radwan A. E., 2021-Radwan, 2021c; Radwan et al., 2021a-Radwan et al., 202e). The measured bottom hole temperature data was used to validate the thermal history model for the two wells, and the measured data of vitrinite organic matter reflectance (% VRo) was utilized to calibrate the model. The temperature history of the sediments along with the wells and burial history modeling were created by basin modeling software that was provided by Gulf of Suez petroleum company (GUPCO). Sedimentation history, deposition timing, and formation age were the key inputs into basin modeling for the geopressured zones. In addition, drilling events and reservoir pressure were employed to validate the PPFG model output results. Schlumberger charts were used for environmental corrections for the logging data set (Charts, 1991). Overpressure generation mechanisms in El Morgan oil field were inferred from the relation between sonic velocity and density (Hoesni, 2004).

The proposed multidisciplinary geopressure evaluation workflow

The proposed multidisciplinary PPFG analysis workflow is dependent mainly on the integration of indirect methods (geophysical methods), measured reservoir data, and drilling event-based interpretations. In addition, basin modeling is integrated with the previous methods, where it represents an effective tool for sedimentation rate determination and overpressure prediction. This workflow goes through five procedures: a) data collection, b) summarizing the data and quality control, 3) calculation process, 4) model result calibration, and 5) final model results. Geophysical data, basin modeling, drilling data, and reservoir measurements are the primary inputs in this approach (Figure 6).

FIGURE 6

Results and discussion

In this study, the studied well logs cover more than 16 km (cumulative well logs) and represent eight wells in the El Morgan oil field, with each well having a thickness of about 2 km. The results of basin modeling, pore pressure, fracture pressure, and overpressure generation mechanisms are discussed as follows:

Basin modeling

Basin modeling, according to Duppenbecker et al. (2004) and Radwan et al. (2020a), can be used to predict and understand pressure evolution or porosity anomaly expectations. Integration of geological, geophysical, and geochemical data allows for establishing a sequential record of basin history changes through the sedimentation process (Poelchau et al., 1997; Thomsen, 1998). As a result, basin modeling can be used as the main key indicator as a quantitative tool for pore pressure prediction, in addition to routine petroleum system evaluation. Moreover, understanding the sedimentation history in the basin can lead to enhancing the abnormal pressure prediction.

The penetrated subsurface section of the El Morgan oil field contains sediments from the Langhian to the Quaternary periods (Figure 4). The developed burial history for the studied field has been converted to equivalent pressure mud density using the PetroMod© (V. 2018). In this study, a thermal history for well A was constructed (Figure 7). In the Gulf of Suez, the temperature history is controlled by the heat flow and subsidence generated by the clysmic tectonic events during rifting stages (Prosser, 1993). The temperature was estimated using 1D basin modeling and confirmed using the actual bottom hole temperature (Figure 7) calculated using the generalized Horner method (Kutasov and Eppelbaum, 2005). Consequently, the constructed one-dimensional burial history for the studied area indicated high sedimentation rates which generated overpressure in the late Miocene formations (South Ghraib and Zeit). Following the relation between depth in feet versus the equivalent pressure density within the sediment for each formation, equivalent pressure build-up was detected against the base of Zeit and South Ghraib formations up to 10.5 ppg (Figure 8).

FIGURE 7

FIGURE 8

More than 700 m (2,296 feet) of sediments were buried in the El Morgan oil field in less than 3 million years during the Tortonian and Messinian periods, indicating a high tendency for compaction disequilibrium to occur in the late Miocene sediments. Figure 8 shows the relation between depth in feet with the equivalent pressure density within the sediment for each formation; the base of the Zeit formation and the South Ghraib formation showed equivalent pressure build-up of more than 10.5 ppg (Figure 8). Pore pressure predictions show that the overpressure is showing a significant deviation in the interval between 975 m (3,200 feet) and 1,525 m (5,000 feet). This fast sedimentation process gives a build-up of overpressure that reflects disequilibrium compaction of the shale due to the high sedimentation rate and fast sediment burial. To properly interpret and predict pore pressure at the studied oil field, velocity and density must be investigated for overpressure generation mechanisms detection. The results of basin modeling analysis in El Morgan oil field are relatively similar to the results of the neighboring Badri oil field, where they have relatively the same geological conditions.

Vertical stress, pore pressure, and fracture pressure analysis

In the investigated eight wells, overburden or vertical stress was found to have an average of 18 ppg equivalent mud weight (EMW) (Figure 9). The overburden gradient increases from 0.91 PSI/feet at the top of the Zeit Formation to 0.98 PSI/feet at the base of the Kareem Formation. The compressional slowness was able to detect the overpressure zone through the late Miocene sediments in the absence of resistivity log. Measured reservoir pressure data was used in the interpretation and calibration of the PPFG model. On the other hand, all encountered drilling problems were documented in Table 1, which was used as an indicator for excess pressure.

FIGURE 9

The pore pressure started as normal pressure with 0.45 PSI/feet at sea bed sediments to the Zeit Formation, then the pore pressure gradient increased by 0.09 PSI/feet and reached 0.54 PSI/feet at a depth of 1,030 m. Pore pressure development continued in the Turonian sediments and reaches up to 0.54 PSI/feet. Most of the Serravalian Belayim Formation prevailed normal pore pressure with a gradient of 0.45 PSI/feet except the top part that has the reservoir interval (Hammam Faraun Member). The Hammam Faraun Member sandstone shows subnormal conditions based on reservoir measurements with a gradient of 0.34 PSI/feet. Reservoir measurements show a subnormal condition in the Kareem Formation with a gradient of 0.29 PSI/feet. Mild-overpressure was developed in the Serravalian shales and reaches up to 9.4 ppg with a gradient of 0.50 and 0.49 PSI/feet in the Hammam Faraun and Kareem Formations, in an arrangement. The current pore pressure, overburden stress, and fracture pressure dataset of El Morgan oil field was documented in Tables 2, 3. Table 2 shows the results in ppg equivalent mud weight, while Table 3 shows the results in PSI/feet. The pore pressure and fracture pressure were modeled in this work to reflect the shale and sandstone pressures, but it does not reflect the pore pressure in other lithologies.

The studied eight wells are classified as development wells, which were drilled through the explored middle Miocene reservoirs in the El Morgan block. Several drilling complexities in terms of salt creeping, tight spots, losses, formation fluid influxes, and wellbore failures are observed in the studied wells. The interpreted PP indicated that the top part of the sediments from the sea bed till late Miocene age sediments display hydrostatic pore pressure equal to 8.7 ppg (EMW). At the base of the Zeit formation and starting from a depth of 1,030 m (3,379 feet) to the base of the South Gharib formation (Tortonian), sonic log response deviates from the NCT, this zone indicating hard overpressure. In addition, two influx events were reported from these layers and the kill mud weight was considered in the PP interpretation (Table 1). The interpreted PP in the base of the Zeit Formation is equal to 10.3 ppg (EMW), while it is equal to 10.5 ppg (EMW) in the South Gharib Formation. Because this zone is a sandstone reservoir zone, PP gives misleading values when using Eaton’s equation at the top of the Belayim Formation (i.e., the Hammam Faraun Member). Therefore, PP interpretation of this reservoir zone was solely based on measured (MDT) data. Prolonged production and depletion have reduced the PP to sub-hydrostatic levels, with pore pressures of 6.5 ppg (EMW) and a gradient of 0.34 PSI/feet. On the other hand, the shale intervals indicated mild overpressure equivalent to 9.4 ppg (EMW), hence it still keeps the virgin pressure of the reservoir (2537 PSI) at a depth of 1,554 m (5100 feet) with a gradient of 0.50 PSI/feet. The three members of the Belayim Formation (Feiran, Sidri, and Baba) display normal hydrostatic conditions with a gradient of 0.45 PSI/feet. The middle Miocene (Kareem Formation) shows subnormal conditions, and the sandstone reservoir pore pressure is 6 ppg (EMW) with a gradient of 0.29 PSI/feet, while it comprises mild overpressure in the shale intervals equivalent to 9.4 ppg (EMW). Therefore, it still keeps the virgin pressure of the reservoir (2990 PSI) at a depth of 1859 m (6100 feet) with a gradient of 0.49 PSI/feet.

Fracture pressure was estimated from Eq. 3, and it shows matching with the FIT data (Figure 9). Fracture pressure gradient decreases against the depleted middle Miocene reservoirs and possesses a risk of fracturing if a higher mud pressure is used while drilling. Digital numbers of the estimated overburden, pore pressure, and fracture pressure were documented in Tables 2, 3. Figure 9 represents the PPFG model output of the studied wells. Sandstone PP only is drawn in the reservoirs section. When the pore pressure profiles of the northern (A, B, C, and D) and southern (E, F, G, and H) El Morgan oil field wells are compared, the pore pressure is the same for all formations except the middle Miocene reservoir sections. It should be noted that pore pressure magnitude differentiation in the Middle Miocene reservoirs is related to reservoir connectivity, where the studied wells are located in different compartmentalizations within the field (Figure 5).

Overpressure generation mechanisms

The mudstone compaction trends are slowed or even stopped by disequilibrium compaction, but they do not deviate from them. On the other hand, fluid expansion or overpressure transfer can lead to unloading, which will result in a sonic transit time reversal and little response in density (Figure 2). Disequilibrium compaction during rapid sedimentation of sediments is one of the main mechanisms that contributed to the development of non-hydrostatic conditions in low-permeability layers in the Gulf of Mexico, Australia, South Caspian Basin, Asia, and the North Sea (e.g., Swarbrick and Osborne, 1998; Lee et al., 1999; Carcione and Gangi, 2000; Gutierrez and Wangen, 2005; Berhmann et al., 2006; O’Connor et al., 2011a; O’Connor et al., 2011b). This mechanism is applicable when fluids cannot be expelled out of the fine-grained sediments due to vertical compaction, and consequently, the entrapment fluids will share in the sediment load. The magnitude of abnormal pressure, in this case, is related to permeability, or how the entrapment fluids will move within the rock pores considering the balance between the continuous creation of PP by sediment loading. It is expected that the degree of abnormal overpressure tends to develop at greater depths based on the expected significant decrease in permeability at deeper depths (Neuzil and Pollock, 1983; Marín-Moreno et al., 2013; Luo and Vasseur, 1996).

Other excess-pressure mechanisms are attributed to fluid phase changes and diagenesis of clay minerals (Swarbrick and Osborne, 1998). The diagenetic process of clay illitization occurs at temperatures ranging from 80°C to 150°C (Nadeau, 1985), but the maximum temperature at the Kareem reservoir is 78°C, excluding this process as a candidate for the overpressure generation mechanism in the studied field. Lateral compression is usually common in compressional basins (McPherson and Garven, 1999; Xie et al., 2001), which is not the case here, where the investigated basin is an extensional rift basin, so this process has been also excluded in this case. The reservoir overcharging mechanism (Grauls and Baleix, 1993) was considered in this case as a potential contributor to the overpressure generation. In the El Morgan field, fluid movement from source rocks to the field reservoirs was proven as up-dip migration from the Campanian-Maastrichtian source rocks to the Miocene reservoirs through faults (EGPC, 1996; Radwan et al., 2021c; Radwan, 2022b), which could increase the pore pressure and develop excess pressure in the reservoirs. In such a case, fluid volume and charging rate are the main controlling factors of the overpressure value. In addition, drainage efficiency, pore and fluid compressibility, and reservoir extension all contribute to the generated overpressure value or magnitude. The overpressure magnitude was increased by 0.7 ppg (0.05 and 0.04 PSI/feet) at the reservoir levels, which could be called low-overpressure (Xie et al., 2001). To gain a better understanding of the overpressure generation mechanism in the El Morgan oil field, the density vs. sonic velocity was plotted as per previous studies (Figure 10) (Swarbrick and Osborne 1998; Hoesni, 2004; O’Conner et al., 2011a; O’Conner et al., 2011b; Lahann and Swarbrick 2011). From the cross-plot, disequilibrium compaction was interpreted as the main mechanism that generates overpressure across the Miocene sediments in the El Morgan oil field (Figure 10). The plotted points remain on the loading curve, suggesting that overpressure in the El Morgan oil field is generated by disequilibrium compaction. The plot results are indicative that the higher sedimentation rate in the late and middle Miocene was responsible for retaining the connate water in the shales and thus exerting hard overpressure. Based on the previous plot results, it is inferred that disequilibrium compaction is the main overpressure generation mechanism in the studied area, while the reservoir overcharging mechanism could contribute to the overpressure generation mechanism with lower magnitude at the level of the studied reservoirs.

FIGURE 10

Model uncertainty

The variable burial history of the Gulf of Suez encompasses varying timings and magnitudes of sediment burial, uplift, and hiatus from one area to another. Because of the high variability of the sedimentation conditions, predicting pore pressures is difficult, and evaluating pore pressures is prone to uncertainty. For the studied case, the results were calibrated by the multi-available data, and the estimated pore pressure showed good matching between geophysical and basin modeling analysis of the late Miocene shales, where both of them indicated 10.5 ppg (EMW). On the other hand, there is no uncertainty related to the middle Miocene reservoirs, where it represents the actual measured data for both sandstone intervals as direct measurements and shale intervals as indirect measurements based on the equilibrium theory. Acceptable uncertainty can be found along the stratigraphic section in the studied field, but with no or few implications on the developed PPFG model based on the multi-proxy approach. Hence, the integration of multidisciplinary data from geology, geophysics, reservoirs, and drilling can decrease the uncertainties and lead to a more reliable PPFG model.

Basin modeling, geophysical logging, drilling events based interpretations, and reservoir data integration outstanding features

Pore pressure prediction in exploratory and development wells depends mainly on seismic and basin modeling methods. Once the first well in an oil field has been drilled, well logs are commonly recorded along the drilled section. Geophysical logging data can be used to estimate pore pressure in sedimentary basin drilled wells (Eaton, 1975; Bowers, 2001; Zhang, 2011). Pore pressure estimation using well logging works primarily in mud-rocks, but direct measurement in reservoir sections can also provide accurate pore pressure data in subsurface sandstone rocks. Considering the pressure equilibrium between sand and shale in the virgin basins, measured reservoir data, in this case, is equal to shale pore pressure (Yardley and Swarbrick, 2000; Daniel, 2001). Basin modeling and burial history development are widely used tools for simulating hydrocarbon generation and sedimentation processes that contribute to overpressure distribution (e.g., Mudford et al., 1991; Borge, 2002; Nordgård Bolås et al., 2004; Hansom and Lee, 2005). As a result, basin modeling is the primary tool for providing an informative vision and understanding of sedimentary basin developments, indicating high potential abnormal pressure zones before going through calculation methods to infer pressure magnitudes. Drilling events-based interpretations can help in the calibration process, and it is considered one of the key elements in the PPFG evaluation process, where it represents the actual observations inside the drilled wells (Bowers, 2001; Radwan et al., 2019b). Using one method can result in overestimated or underestimated results, which will have a negative impact on the final PPFG model and deliver high uncertainties in the developed PPFG model.

The developed approach in this work can be applied in PPFG studies for both development and exploratory geomechanical studies within other fields of the Gulf of Suez basin or elsewhere in the world. The presented approach has the advantage of being a multidisciplinary approach that integrates the geological basin analysis, recorded logs, drilling problem based interpretations, and reservoir measurement data to enhance the understanding of subsurface pore pressure behavior in a specific region. Consequently, the benefits of this integrated data are the following: 1) The proposed integrated pore pressure evaluation approach could lead to a boost in the pore pressure evaluation process; 2) it has the potential to reduce the uncertainty of the geopressure model and lead to a more accurate one; and 3) it has the potential to aid in the determination of more reliable casing seats, which has implications for successful drilling operations. The limitation of this approach is the lack of any tool from previously collected data, which may be the case in many regions, making the PPFG development less accurate to some extent.

Conclusion

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