Nodal Analysis of Naturally Flowing Wells in Faihaa Oil Field, Yamama Formation

Abstract


Introduction
Well performance analysis is essential in the petroleum industry for optimizing oil production and ensuring efficient reservoir management.By analyzing the performance of oil wells, operators can identify any decrease in production rates and take appropriate measures to maintain or improve performance (Biantoro et al., 2022, Ottba andAl-Jawad, 2006).This analysis helps in determining the production capacity of the well and optimizing the pump speed to achieve the desired flow rate (Ortiz Requena et al., 2021).Additionally, well performance analysis allows for the identification of potential issues such as water loading, which can lead to premature inactivation of wells (Meng et al., 2021).By implementing improved practices based on well operating conditions, operators can maximize the natural life cycle of oil wells and ensure compliance with production quotas.Overall, well performance analysis is crucial for optimizing oil production, prolonging well life, and maximizing reservoir management efficiency (Ortiz Requena et al., 2021).

Geology of the Studied Field
The Faihaa oil field is located in southern Iraq, around 20 km north of Basra city, and is parallel to the Iraq-Iran border as shown in Fig. 1.The field is bounded by the Majnoon oil field to the north, the Sindbad oil field to the south, the Nahr Omar oil field to the west, and the Iranian Hosseinieh (Yadavaran) field to the east.The oil field is an anticline, thickened, upright, branchy fold structure with a plunge of the hinge line between 4 and 4.2 degrees in the northwest direction and an axial surface angle of 89.7°.It is an asymmetrical structure with the western limb of the fold shorter than the eastern limb.The area of the field is about 900 km 2 (Mohammed et al., 2022).
The Faihaa oil field was discovered by Kuwait Energy on February 3, 2013, in the northeast of Block 9 within the Zubair subzone of the southeastern part of the Mesopotamian basin (Kareem et al., 2021).The field is classified as a structural trap and is represented by an anticlinal fold with double plunging (Al-Aani et al., 2020).The Yamama Formation is present in the field, and a geological model has been constructed for it (Al-Aani et al., 2020).The thickness parameter of the fold indicates that there are two types of folds, thickened fold (Yamama, Hartha) (Lazim et al., 2022).The Yamama Formation is a significant carbonite reservoir in the south of Iraq, and it is considered one of the most important productive reservoirs in the region.The lithology of the Yamama Formation is primarily composed of limestone, with some dolomite and secondary porosity indication (Chafeet, 2016, Al-Iessa andZhang, 2023).The formation is characterized by porous limestone interspersed with thin layers of argillaceous and tight limestone (Al-Iessa and Zhang, 2023).The Yamama Formation is located at a depth of about 3499-4100 m below sea level and is surrounded upward by the Ratawi Formation and underlain by the Sulaiy Formation, with a thickness of up to 400m (Chafeet, 2016, Mohsin et al., 2022).Yamama Formation is at a depth of about 3499-4100 m under the sea level and is Surrounded upward by the Ratawi Formation and underlain by the Sulaiy Formation with a thickness is up to 400m (Jassem and Goff, 2006, Saleh, 2014, Mohsin et al., 2022).while its maximum thickness in the study area reaches almost 324 m at well Fh-1 as shown in Fig. 2 and Fig. 3.
The Yamama Formation is an important reservoir as well as a good source rock in many of the oilfields of the southern Mesopotamian Basin, Iraq (Al-Khafaji et al., 2022).It has the ability to contribute to generating and expelling petroleum to Cretaceous reservoirs of the Mesopotamian Basin, Iraq (Al-Khafaji et al., 2022).The formation comprises outer shelf argillaceous limestones and oolitic, pelloidal, pelletal, and pseudo-oolitic shoal limestones (Chafeet, 2016).Microfossils such as foraminifera and calcareous algae have been identified in the Yamama Formation (Mohsin et al., 2022).By studying the biostratigraphy and depositional environment of Yamama Formation in the Faihaa oil field and by using both benthic foraminifera and green calcareous algae in the determination of biostratigraphic zonation and the formation age, the formation is assigned to the Berriasian-Valanginian age and six biozones were discovered.The six observed biozones are Charentia cuvillieri sp., Psudochryalidina infracretacea sp., Pseudocyclammina Lituus sp., Nezzazata Perforate sp. and Choffatella sp., Desycladales Green Algae-Cylindroporella sp. and Desycladales Green Algae-Salpingoporella cf.circassa sp., (Al-Hassani and Al-Dulaimi, 2021).Microfacies and biostratigraphy of the Yamama Formation and based mainly on benthic foraminifera fossils were also studied and investigated in selected wells in southern Iraq.By examination of more than 250 thin sections of the core samples from the studied wells, different diagenetic processes and environments that affect the reservoir quality of the Yamama Formation in the Faihaa Oil Field were identified.The marine, meteoric and burial environments were the main identified diagenetic environments that affected the Yamama reservoir.Eight diagenetic processes were observed in Yamama Formation and showed both positive and negative impacts on reservoir quality; Both dissolution and fracture diagenetic processes had a significant beneficial impact on reservoir quality by producing and enhancing porosity and permeability.Cementation and compaction processes have a negative impact on reservoir quality by reducing both permeability and porosity.Other processes, such as micritization, bioturbation, neomorphism, and dolomitization, have little impact on reservoir quality.According to the genetic categorization of porosity, the majority of porosity inside the Yamama reservoir was generated by diagenesis processes, meaning that it is a kind of diagenetic reservoir (Ahmed et al., 2020).3D geological model of the Yamama reservoir in the Faihaa oil field shows that the formation is divided mainly into four units (YA, YB, YC, and YD), and each one of these main units is also divided into secondary units.YA has five secondary reservoir units (YA1, YA2, YA3, YA4, and YA5), both YB and YC have two secondary reservoir units (YB1, YB2, YC1, and YC2) respectively, finally, YD has three secondary reservoir units (YD1, YD2, and YD3).According to data analyses and the results from petrophysical models for each subunit of the Yamama reservoir, the YA and YB are considered the best and most important oil-bearing subunits in the Yamama reservoir because it has good petrophysical properties (high effective porosity and hydrocarbon saturation) (Al-Aani et al., 2020).

Materials and Methods
To achieve the goals of this study, reservoir, well, and PVT data have been utilized, along with the PIPESIM software tool, to construct IPR and VLP curves.Then, well sensitivity analysis using nodal analysis has been performed at the bottom hole node on various parameters.The data used in this study includes PVT data that depend on the type of fluids in the reservoir, well data that relates to the completion and design of the well, and reservoir data obtained during drilling and well testing operations, which are listed in Tables 1 to 3.

Methodology
The nodal analysis method was employed in this study using PIPESIM 2017, a powerful software tool developed by Schlumberger that is widely used in the petroleum industry (Al-Juboori et al., 2020 andAl-Janabi et al., 2021).In this study, the production system was partitioned into nodes, with the bottom hole designated as the primary node, to perform sensitivity analysis on critical system components and parameters, such as production tubing size, WHP, water cut, and reservoir pressure.
The primary objective was to identify the variables and components that may contribute to production issues and determine the optimal values for each variable to improve production efficiency.The initial state of well deliverability was established under natural flow conditions and well configuration by constructing IPR and VLP curves.The intersection of these curves was used to determine the operating point of the well, indicating the safe flow rate that can be produced and delivered.
By using the available data from well completion reports as illustrated in Table 2, well configurations for the FH-1, FH-2, FH-3, and FH-4 wells have been constructed (downhole equipment, wellbore geometry) as shown in Figs. 4 to 7. Several methods have been used in the literature to predict the IPR curve, including those developed by Vogel (1968), Wiggins et al. (1992), Gasbarri et al. (2009).For the VLP curve, different multiphase flow-pressure drop correlations, such as those developed by Hagedorn andBrown (1965), Duns Jr andRos (1963), Orkiszewski (1967), Aziz and Govier (1972), Beggs and Brill (1973), and Gray (1974), are used.However, no single correlation has been proven to work for all field conditions and parameters, so various multiphase flow correlations should be used with different parameter ranges to avoid significant errors (Al-Fatlawi et al., 2015).

Results and Discussion
Several models are available in the PIPESIM software for constructing IPR curves, including (Well PI, Vogel, Fetkovitch, Jones, Back pressure, Darcy, Forchheimer, and Hydraulic fracture) each of these models requires specific type of data and can be used in different situations.In the case study for all wells, the productivity index's equation (PI= q/(Pr-Pwf)) has been used in inflow relationships higher than the bubble point pressure (Pb), and the Vogel empirical solution has been used in the case of pressure is lower than the bubble point pressure to construct (IPR) curve.The IPR curves for the wells (FH-1, FH-2, FH-3, and FH-4) have been constructed based on the PVT data and reservoir field data, which are listed in Table 1 and Table 3.These curves are shown in Figs.8 to 11.The production rates of the four wells are analyzed under natural flow conditions and an original tubing inside diameter of 2.922 in.These rates are (5462, 5295, 2044 and 9567 STB/d) for wells (FH-1, FH-2, FH-3, and FH-4) respectively, as shown in Fig. 12 which are represented by the intersection point of IPR and VLP curves.Wells FH-1 and FH-2 demonstrate a very good production rate, safely operating within the operation envelope.Well FH-3, although it has good reservoir properties, produces at a lower flow rate.Well FH-4, on the other hand, exhibits an extremely high flow rate, with the two curves intersecting outside the operating envelope.This indicates unstable and potentially damaging production, which could affect the other wells and the separation equipment if it connects to the same manifold.To address these production problems, a well-sensitivity analysis is required on four variables: production tubing size, water cut, reservoir pressure, and WHP.This analysis aims to understand the effects of these variables on production and determine the optimal values for each variable to solve the associated production problems.

Effect of Tubing Size
After selecting the bottom hole as the solution node, a sensitivity analysis is performed on the tubing size to determine the best size for efficient well production.The tubing string is a crucial component of each well completion, and selecting the appropriate size is essential for efficient fluid flow or the installation of appropriate artificial lift equipment.Table 4 lists the calculated flow rates for different flowing tubing diameters.These results show that the flow rate increases as the tubing inside diameter increases, but as the inside diameter further increases, the holdup effect becomes more significant.This is due to releasing more gas into the fluid column as a result of pressure drop.This phenomenon should be noticed and taken into consideration, as it affects the bubble point pressure.Additionally, as the tubing's inside diameter increases, the erosional velocity ratio of the pipe decreases.This ratio should be far away from one, which is the recommended value.By examining the data for wells FH-1, FH-2, and FH-4 (Fig. 13a, Fig. 13c, Fig. 13g) respectively, it can be observed that these increasing tubing sizes cause the inflow curve to intersect the outflow curve at its flat region, representing an unstable flow region.This instability can lead to various issues, such as reduced production efficiency and potential damage to the well infrastructure.For Well FH-3 (Fig. 13e), when the tubing inside diameter changes to 3.958 in, 4.126 in, and 4.25 in respectively, the liquid flow rate will increase slightly by a negligible amount.This indicates that in this well, changing the tubing size has a minimal influence on increasing production.Therefore, for this well, tubing with an outside diameter of 3.5in and an inside diameter of 2.992in will be considered, as it provides stable production without any problems for all wells.

Effect of Water Cut
The effect of water cuts on the well performance analysis for the four wells is illustrated in Fig. 14.Increasing water in the flow path causes a decrease in oil flow rate due to its influence on the mixture density.This increases slippage between two phases and increases hydrostatic head.The liquid flow rate decreases to 985 STB/d, 1867 STB/d, and 11 STB/d when the water cut reaches 80 %, 60%, and 70% in FH-1, FH-2 and FH-3 wells respectively.When the water cut reaches 90 %, 70%, and 80% respectively in these three wells there is no more intersection between the IPR and VLP curves (Fig. 14a, Fig. 14b, Fig. 14c), which means that these wells can't produce more should be closed.For the well FH-4 (Fig. 14  d), when the water cut increased to 50 %, 60 %, and 70 %, the well still produced oil in satisfying quantities.However, 80% and 90% water cut caused the oil production rate to decrease compared to the original production rate in the early life of the well when the water cut was 0 %. (Fig. 14d) shows that the FH-4 well still produces even though the water cut becomes 100 %, and in that case, all produced fluid will be water.In general, we can say 50 % water cut and above result in useless and unprofitable production.Therefore, it's important to avoid water cut percent to reach 50%.All the results for the water cut sensitivity analysis for the four wells are listed in Table 5.

Effect of Reservoir Pressure
Reservoir pressure depletion has a significant impact on the production rate of wells.Fig. 15 shows the effect of reservoir pressure on the performance analysis for the four wells.When the reservoir pressure decreases, the curvature of the IPR curve diminishes and the production rate decreases.For the four wells, the production will be stopped, and the wells will die when the reservoir pressure decreases from its original value to 6000 psi, 6500 psi, 6500 psi, and 5000 psi respectively.This is because there is no intersection between the inflow and outflow curves as shown in Fig. 15a to Fig. 15d, and Table 6, This is the suitable time to implement artificial lift methods such as gas lift, electrical submersible pump, or water injection to ensure the continued production of these wells.

Effect of Wellhead Pressure
Fig. 16 and Table 7 show the effect of WHP on the well performance analysis for the wells FH-1, FH-2, FH-3, and FH-4.Based on these results, it can be concluded that the WHP has a significant impact on the performance of the well.When the WHP was reduced from its original amount, more fluid was produced, and the VLP curve showed better performance.Conversely, when the WHP was increased, the VLP curve gave a lesser performance, and when the WHP was increased to a certain value at which there was no intersection between the two curves, it means the well couldn't have produced with that WHP.The WHP is chosen in a way that ensures the flow velocities remain under the erosional limit.For FH-1, the original WHP of 2310.7 psi gives the best result and optimum well performance, producing a 5461.7 STB/d liquid rate.When the WHP was decreased to 1000 psi, the liquid rate increased to 8387 STB/d, but the operating point was located out of the operation envelope, and the maximum erosional velocity ratio (EVR) max=1.83,which means the well produces 8386.548STB/d with a problem and not in a safe manner.When the WHP was increased to 3000 psi, the production rate of liquid decreased to 3527 STB/d, and the EVR max also decreased to 0.51.When it was further increased to 4000 psi, there was no intersection point between the two curves, which means the well couldn't have been produced with that WHP.
For the well FH-2, decreasing the WHP to 2500 psi will increase the liquid rate from 5294 STB/d under the actual WHP to 6620 STB/d, but this decreasing WHP causes the operating point to be out of the envelope, which is not desirable.Therefore, the WHP will be kept at its original value because it gives the most optimized production.For the FH-3, if the WHP changes to 1000 psi, the rate will increase to 5583 STB/d, and the maximum erosional velocity ratio (EVR max) will be 1.21, which is above the acceptable value.WHP of 1500 psi caused production to increase to 4779 STB/d with an operating point inside the envelope and a perfect EVR max value of 0.87.Therefore, of the five WHP values, the 1500 psi WHP is the optimum value that optimizes the production of that well.For the case of the well FH-4, if the WHP is reduced to 1500 psi, the situation will worsen and become more complicated as the flow rate increases to 10689 STB/D.Increasing WHP will make things better, and 3500 psi will have a reduced liquid flow rate to 5675 STB/d but fix the location of the operation point with respect to the envelope and adjust the EVR max value to 0.88.Therefore, 3500 psi WHP will be the most optimum value that fixes the situation and causes safe and optimized production from that well.

Conclusions
Well performance analysis by using PIPESIM software is a very powerful and crucial method as it is used to optimize production rate and allows engineering to assess the productivity and efficiency of oil and gas wells but it's not as effective as the decline curve analysis method in the determination of the time in which the flow rate will decline until the reservoir is depleted.Based on the results of this study, the following conclusions have been drawn: The performance analysis process takes into consideration the change of some variables which included: production tubing inside diameter, wellhead pressure, water cut, and reservoir pressure to determine the conditions for the best working efficiency.From the results we obtained that the wellhead pressure is the main variable we can adjust to optimize well performance.For well FH-3, the optimized wellhead pressure is 1500 psi instead of 3176 psi.For FH-4, 3500 psi instead of 2075 psi wellhead pressure will be chosen to solve the production problem of that well.
For study wells, the maximum value of the water before the natural flow period comes to an end as a result of non-intersection points are 80%, 70%, 70-80%, and 100% respectively which is extremely high range of values, so the matter of water cut percentage increment should always be put into consideration, so prevention and preparation should be taken to avoid a sudden increment in the produced percentage of water, which might lead the well at a certain time to have more water production compared to hydrocarbon production.
Generally, the sensitivity analysis shows that the 3.5 in.production tubing size is suitable for rates ranging from 5000 to 7000 STB/d which means it's the optimum tubing size in our case study.

Fig
Fig. 16.a) Results of WHP sensitivity analysis for Well FH-1; b)Well FH-1 performance when WHP=1000 psi; c) Results of WHP sensitivity analysis for Well FH-2; d) Well FH-2 performance when WHP= 2500 psi; e) Results of WHP sensitivity analysis for Well FH-3; f) Well FH-3 performance when

Table 2 .
Well data for the for the FH-1, FH-2, FH-3, and FH-4 wells in Faihaa Oil Field

Table 4 .
Results of system sensitivity analysis with different tubing sizes

Table 6 .
Results of system sensitivity analysis for reservoir pressure depletion

Table 7 .
Results of system sensitivity analysis for different WHP