The Jeribe Formation, the Jambour oil field, is the major carbonate reservoir from the tertiary reservoirs of the Jambour field in northern Iraq, including faults. Engineers have difficulty organizing carbonate reserves since they are commonly tight and heterogeneous. This research presents a geological model of the Jeribe reservoir based on its facies and reservoir characterization data (Permeability, Porosity, Water Saturation, and Net to Gross). This research studied four wells. The geological model was constructed with the Petrel 2020.3 software. The structural maps were developed using a structural contour map of the top of the Jeribe Formation. A pillar grid model with horizons and layering was designed for each zone. Following the porosity model, the average porosity was roughly 11%. According to the permeability model, the reservoir has average permeability of 150 md while average net to gross, water saturation and thickness were 54%, 61%, and 75.5m, respectively. Depending on the average values of each unit separately zones two and three had good petrophysical characteristics, with about 85% of the Jeribe reservoir containing hydrocarbons.

The development of tight reservoirs using a horizontal well requires caution owing to the reservoir sensitivity to stress. Predicting the horizontal wellbore instability during reservoir depletion is critical for tight reservoirs. The present study investigated the wellbore failure criteria and stress orientation changes with reservoir depletion of a horizontal well in a tight reservoir, considering rock sensitivity to stress with pressure reduction. An integrated reservoir model coupled with geomechanics was used to predict pore pressure. A mechanical earth model (MEM) was constructed to examine the stability of horizontal wells. The unconfined compressive strength (UCS) was correlated with changes in porosity due to stress changes. The MEM shows that the failure criteria around the horizontal wellbore, including breakout, loss, and breakdown pressures, change considerably with reservoir depletion. A more significant response was observed in the stress-sensitive layer, which was characterised by a higher permeability. The safe mud weight window of the studied horizontal well narrowed significantly after production for five years, whereas the stability was completely absent after ten years. The deterioration of stability with depletion is governed mainly by permeability reduction, which may cause severe pressure reduction, whereas the stability improvement due to the increase in UCS caused by porosity reduction seems marginal. Relatively small changes in the direction of the stresses around the wellbore with depletion were observed, with the stress distribution concentrated in the predominant direction as the depletion continued. This study indicates that the sensitivity of petrophysical and geomechanical properties to stress amplifies the instability in tight reservoirs, particularly around wellbores.

The Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units. This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized porosity log-log plot reveals the presence of three distinct Hydraulic Flow Units and corresponding rock types within the Jeribe reservoir. These rock types can be identified if known. The reservoir can be divided into three groups of rock types, namely good, moderate, and bad quality. The bad rock type represents a restricted section within the reservoir, while the upper and lower parts predominantly consist of moderate-quality rock types. Conversely, the central section of the reservoir exhibits a good-quality rock type. By utilizing the Flow Zone Indicator principles, this study provides valuable insights into the hydraulic flow behavior and rock types present in the Jeribe reservoir. The proposed permeability model derived from this method can aid in predicting permeability values for uncored wells, contributing to a better understanding of the reservoir's heterogeneity and facilitating reservoir characterization and management decisions.

Capillary pressure is a significant parameter in characterizing and modeling petroleum reservoirs. However, costly laboratory measurements may not be sufficiently available in some cases. The problem amplifies for carbonate reservoirs because relatively enormous capillary pressure curves are required for reservoir study due to heterogeneity. In this work, the laboratory measurements of capillary pressure and formation resistivity index were correlated as both parameters are functions of saturation. Forty-one core samples from an Iraqi carbonate reservoir were used to develop the correlation according to the hydraulic flow units concept. Flow zone indicator (FZI) and Pore Geometry and Structure (PGS) approaches were used to identify the reservoir hydraulic flow units. The experimentally derived correlations can be used to predict capillary pressure from resistivity, which is widely available from well-logs. FZI and PGS rock typing methods were applied to characterize the reservoir rock types. For both methods, the log-log plot of Leverett J-function and capillary pressure versus resistivity index for each rock type represent a power-law model relationship between these parameters. Despite the good permeability-porosity prediction results, the FZI approach did not yield a good correlation between J and I. PGS resulted in a better performance in terms of both permeability-porosity prediction and Pc with I correlation because PGS honors the pore geometry and structure relationship with the mean hydraulic radius more than FZI. This work introduces a new correlating approach that aims to assist in reservoir characterization and simulation.

The Material Balance Equation is a crucial tool utilized in reservoir studies to evaluate fluids and rock properties at static pressures. The Flowing and Dynamic Material Balance methods offer a significant advantage by avoiding the requirement to shut down wells, as they use flowing pressure instead of static pressure under constant or variable flow rates. The concept of "Dynamic Material Balance" involves converting the bottom hole flowing pressure at any point at any given time to the average reservoir pressure at that point. This allows for the use of classical material balance calculations and the development of classical material balance plots. In this study, the Dynamic Material Balance and Agrawal Type Curve techniques were used to estimate average reservoir pressures, initial hydrocarbon in place, and ultimate oil recovery for a well in the Mishrif reservoir, the main reservoir in the Buzurgan oil field. Many wells in this field experience problems such as high-pressure decline or continuous water production, necessitating ongoing evaluation. While the Dynamic Material Balance method focuses on boundary-dominated flow data, the Agrawal-type curve technique analyzes data from both transient and boundary flow periods. Agarwal decline curves were constructed using relationships of pseudo pressure normalized production, material balance pseudo time, and dimensionless variables in well-test analysis. The results from both methods showed comparable results with an absolute percentage error of (0.738) %, (3.07) %, and 5.7% for oil-in-place, drainage area, and average reservoir pressure, respectively. This strong correlation between the Dynamic Material Balance and Type Curve results indicates their accuracy and reliability.

Qaiyarah oil field is characterized by its complexity due to its extra heavy oil reaching 16° API. Thus, building a systematic PVT model for this field at a specific range of temperatures is a powerful challenge for screening such reservoirs. The peng-Robenson equation of state model with up to six pseudo components was developed for the crude sample of the Qaiyarah oil field. This work represents the fingerprint for constructing a dynamic model for the field under study. The model also applies to the heavy oil reservoirs under splitting and lumping scenarios. This work suggests a lumping scheme to enhance the accuracy and CPU performance of compositional reservoir simulations. Therefore, the full components model (13 components) is lumped into a reduced number of pseudo components (6 components) to be utilized in the compositional fluid simulation. This study outlines the Peng-Robinson equation of state (EOS) to tune the data at a certain pressure range up to 400 psi. More specifically, various essential parameters have been trained to match the model results with the experimental data. Splitting processes of C6+ into four pseudo components, namely, HYP01, HYP02, HYP03, and HYP04 is added to the matching picture. Separately, justifying the critical properties introduced a better result of regression. The results showed an acceptable match for Bo with an error percent below 1%, while calculated oil viscosity deviated from measured values in different ranges against pressure variation.

This study utilizes streamline simulation to model fluid flow in the complex subsurface environment of the Mishrif reservoir in Iraq's Buzurgan oil field. The reservoir faces challenges from high-pressure depletion and a substantial increase in water cut during production, prompting the need for innovative reservoir management. The primary focus is on optimizing water injection procedures to reduce water cuts and enhance overall reservoir performance. Three waterflooding tactics were examined: normal conditions without injectors or producers, normal conditions with 30 injectors and 80 producers and streamline simulation using the frontsim simulator. Three main strategies were employed to streamline water injection in targeted areas. Over a 22-year forecasting period and employing seven Strategies, streamline simulation were optimized both oil and water outputs. The hybrid Strategy-7 as mixed between all three outperformed Strategy-1 that was gave highest optimization result for only one strategy, yielding the highest cumulative oil production of 1281 million stock tank barrels, the highest oil recovery factor of 24.1%, and a minimal of 2.5% water cut. This study underscores the importance of streamline simulation in managing reservoirs under challenging subsurface conditions, highlighting that a thoughtful integration of streamlining tactics can significantly improve reservoir performance even enhancing oil recovery and addressing water-related issues. The findings contribute valuable insights for optimizing waterflooding strategies in similar globally geological contexts.

In petroleum reservoir engineering, history matching refers to the calibration process in which a reservoir simulation model is validated through matching simulation outputs with the measurement of observed data. A traditional history matching technique is performed manually by engineering in which the most uncertain observed parameters are changed until a satisfactory match is obtained between the generated model and historical information. This study focuses on step by step and trial and error history matching of the Mishrif reservoir to constrain the appropriate simulated model. Up to 1 January 2021, Buzurgan Oilfield, which has eighty-five producers and sixteen injectors and has been under production for 45 years when it started in 1976. Reservoir exhibits heterogeneity in porosity and permeability throughout the field, therefore it’s a big challenge to control all reservoir properties during matching process. The historical matching process includes matching field and wells oil and water production rates, water injection rates, water cut, and reservoir static pressure. Finally, the results show that the good matching between simulated model and observed data; oil and water production rates, water injection rates, water cut, and static reservoir pressure which allow for implementing perfect future production forecasting strategies.

The term "tight reservoir" is commonly used to refer to reservoirs with low permeability. Tight oil reservoirs have caused worry owing to its considerable influence upon oil output throughout the petroleum sector. As a result of its low permeability, producing from tight reservoirs presents numerous challenges. Because of their low permeability, producing from tight reservoirs is faced with a variety of difficulties. The research aim is to performing hydraulic fracturing treatment in single vertical well in order to study the possibility of fracking in the Saady reservoir. Iraq's Halfaya oil field's Saady B reservoir is the most important tight reservoir. The diagnostic fracture injection test is determined for HF55using GOHFER software. Models for petrophysics and geology were calibrated using the diagnostic fracture injection test results after the petrophysical and geomechanical parameters of the rock have been determined. The HF55 vertical well, which penetrates the Saady reservoir, has well logs that have been used to evaluate the petrophysical and geomechanical parameters. These estimates have been supported by findings from the diagnostic fracture injection test through the utilization of standard equations and correlations. The findings of the diagnostic fracture injection test, often known as the diagnostic fracture injection test, are very compatible with the findings of the well logs. The diagnostic fracture injection test pre-falloff test event was examined to determine the instantaneous shut-in pressure and fracture gradient. In the meantime, Closure pressure, process zone stress, fracturing fluid efficiency, closure gradient, critical fissure opening pressure, storage correction factor, permeability, and pressure-dependent leak-off coefficient were all determined using the G function on plot. With the help of a specific software, the petrophysical and geomechanical properties of a single vertical well [HF55] was found. Saady B reservoir's upper and lower sections, along with it are therefore predicted to have the full range of petrophysical and geomechanical features. With the use of DFIT analysis, these features serve as the foundation for developing fracturing models.

Prediction of the formation of pore and fracture pressure before constructing a drilling wells program are a crucial since it helps to prevent several drilling operations issues including lost circulation, kick, pipe sticking, blowout, and other issues. IP (Interactive Petrophysics) software is used to calculate and measure pore and fracture pressure. Eaton method, Matthews and Kelly, Modified Eaton, and Barker and Wood equations are used to calculate fracture pressure, whereas only Eaton method is used to measure pore pressure. These approaches are based on log data obtained from six wells, three from the north dome; BUCN-52, BUCN-51, BUCN-43 and the other from the south dome; BUCS-49, BUCS-48, BUCS-47. Along with the overburden pressure gradient and clay volume, which were also established first, data such as gamma ray, density, resistivity, and sonic log data are also required. A key consideration in the design of certain wells is the forecasting of fracture pressure for wells drilled in the southern Iraqi oilfield of Buzurgan. The pressure abnormality is found in MA, MB21, MC1 and MC2 units by depending on pore pressures calculated from resistivity log. In these units, depths and its equivalent normal and abnormal pressure are detected for all sex selected wells; BUCS-47, BUCS-48, BUCS-49, BUCN-43, BUCN-51 and BBCN-52. For MA, MB21, MC1, and MC2 units, the highest difference in pore pressure values are 1698 psi @ 3750 m (BUCN-51), 3420 psi @ 3900 m (BUCN-51), 788 psi @ 3980 m (BUCS-49), and 5705 psi @ 4020 m (BUCN-52). On other hands, MB11 and MB12 units have normal pressure trend in all studied wells. Finally, the results show that the highest pore and fracture pressure values is existed in North dome, in comparison with that obtained in south dome of Mishrif reservoir at Buzurgan oilfield.

Natural fractures provide an important reservoir space and migration channels for oil and gas reservoirs and control the reservoir potential. Therefore, it is essential to understand the methods for identifying accurate reservoir permeability and characterizing reservoir fractures. In particular, using conventional measurements to identify permeability and characterize fractures is very expensive. While using conventional logging data is very challenging, and an efficient characterization correlation method is urgently needed. In this paper, we have evaluated reservoir potential based on the sensitivity of sonic scanner tools to fluid mobility, maximum stress direction, and fractures presence. This tool provides a continuous estimation of these important parameters along the studied formation using a real field data. Dispersion behavior based on the difference between the maximum and minimum energy of the studied formation is used to detect reservoir heterogeneity and anisotropy. Dispersion analysis shows the presence of inhomogeneous anisotropy in several intervals along the studied formation. The methodology used in this paper provides an accurate estimation of reservoir permeability varies from 1 to 100 md. Also, the application of this technique shows an accepted percent error of reservoir permeability estimation reaches to 7% when compared to laboratory core measurements. The average direction of the maximum horizontal stress in the studied formation is detected to be NW10 to N16E. The study results prove that the proposed technique is effective for the identification of important reservoir properties in the oil industry.

Geomechanical properties have a prominent influence on reservoir stresses, which consequently reduce permeability and porosity with pressure depletion. These properties significantly affect the accuracy of reservoir modeling and recovery calculation, but have not been fully studied; therefore, more work is needed. Full field data and laboratory measurements are included in the study. The work involves deriving an equation by combining experimental data for permeability and porosity reduction during a change in stress with the poroelastic stress equation to investigate the impact of Poisson's ratio and Young's modulus on the reduction of permeability and porosity with pressure depletion. Most simulation studies assume constant geomechanical properties across the entire reservoir or for each individual reservoir layer. In this study, three approaches were considered for the Poisson's ratio and Young's modulus in the reservoir model: 1) constant average values assigned to the entire reservoir, 2) constant average values assigned to each layer, and 3) constant values assigned to each grid block. The validity of the model results was checked by history matching with production and pressure data. For the studied tight reservoir, the Poisson's ratio and Young's modulus significantly affected the permeability and porosity reduction with pressure depletion. The impact of Young's modulus was more pronounced than Poisson's ratio. The simulation results for oil rate, cumulative oil production, and water cut for the reservoir and a selected well showed that applying the three suggested geomechanical approaches resulted in a substantial discrepancy in the model outcome. In general, the coupled model with the mapped geomechanical properties resulted in lower oil and water production. This is attributed to the large values of mapped Young's modulus in parts of the reservoir which resulted in large permeability reduction and subsequently lower oil and water production is expected. In contrast lower Young's modulus per layer was obtained due to averaging process. Poisson's ratio effect on fluid production is much less significant due to its small effect on permeability reduction with depletion. Similarly, the adoption of different geomechanical property values for each layer yielded a relatively lower production outcome than when using a constant value for the entire reservoir. The study indicates the importance of considering the detailed description of the reservoir geomechanical properties to obtain reliable simulation results.

A reservoir is formed due to geologic deposition processes and is not created randomly. However, because of subsurface complexity and limited data, there are many uncertainties in reservoir characterization. Uncertainties can be reduced by gathering more data and/or employing improved technology and scientific methods. Under uncertainty and risk, uncertainty analysis should be performed for investigational analyses as well as decision-making. The main focus of uncertainty analysis in reservoir characterization and management should be to understand what needs to be known and what can be known. Therefore, there are several reservoir parameters’ uncertainties and their quantitative influence on cumulative oil production and water cut were studied. In this paper, sensitivity analysis and uncertainty quantification were conducted for several parameters to study their effect on cumulative oil production. The Monte Carlo method was used to carry out the uncertainty quantification. In this study, we examined two methods which are the Monte Carlo simulation using a Reservoir simulator (MCRS) and the Monte Carlo simulation using a Proxy (MCP) to overcome the issue of the high number of simulation runs requirement and to reduce time consumption. The results showed that The MCP method is a very useful and powerful tool to conduct the uncertainty quantification than the MCRS because the MCP performs the objective function with extremely less time-consuming and very accurate and identical results compared to the results of the MCRS method. The results of uncertainty quantification for production forecast show there is a low risk due to the small gap difference between the P50 and P90. While the sensitivity analysis results showed that the oil-water-contact depth is the dominant parameter that affects cumulative oil production while porosity is the less influential parameter.

Three-dimensional static model is a crucial key for a reservoir heterogeneity representation and an initial evaluation of the hydrocarbon in place, thus for a success field development, an accurate reservoir characterization is a fingerprint for the decision making. The initial goal of this study is to generate a static model for Jeribe and Euphrates formations in Qaiyarah oil field to investigate the distribution of the discrete and continuous proprieties such as, permeability and water saturation, in sequence, recognizing the value of the reserve to identity the ability of developing this reservoir as a final decision for future investment. The sever hetrogeneity and complexity of Qaiyarah oil field were the main challenges confronted through the static model building, in consequence, this paper repesents a fingerprint for the future studies in this area. The conceptual methodology in this research includes the integration of the well log data and final well reports to construct the three-dimensional model through log interpretation, sequential simulators, and properties upscaling. Initial volumetric calculations were performed mainly based on the petrophysical properties distribution of eight wells and oil water contact level. Accordingly, the hydrocarbon volume in place were estimated in the two pay reservoirs under study Jeribe and Euphrates formations. The results showed that Euphrates Formation has dominated by the largest portion of reverse (554*106 Sm3), while Jeribe Formation has lower volume of oil initially in place about 194 *106 Sm3.

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in permeability prediction and compared its results with the flow zone indicator methods for a carbonate heterogeneous Iraqi formation. The methodology of the research can be Summarized by permeability was estimated by using two methods: Flow zone indicator and Artificial intelligence, two reservoir models are built, where the difference between them is in permeability method estimation, and the simulation run will be conducted on both of the models, and the permeability estimation methods will be examined by comparing their effect on the model history matching. The results showed that the model with permeability predicted by using artificial intelligence matched the observed data for different reservoir responses more accurately than the model with permeability predicted by the flow zone indicator method. That conclusion is represented by good matching between observed data and simulated results for all reservoir responses such for the artificial intelligence model than the flow zone indicator model.

The estimation of the initial oil in place is a crucial topic in the period of exploration, appraisal, and development of the reservoir. In the current work, two conventional methods were used to determine the Initial Oil in Place. These two methods are a volumetric method and a reservoir simulation method. Moreover, each method requires a type of data whereet al the volumetric method depends on geological, core, well log and petrophysical properties data while the reservoir simulation method also needs capillary pressure versus water saturation, fluid production and static pressure data for all active wells at the Mishrif reservoir. The petrophysical properties for the studied reservoir is calculated using neural network technique from 13 cored and logged wells. The results showed that the reservoir simulation method gave a value of Initial Oil in Place that agrees and close to the value of Initial Oil in Place obtained from the volumetric method with a percentage different around 2%. However, the estimation of Initial Oil in Place by reservoir simulation method offered accurate results during good history matching with observed data as well as making appropriate adjusting for Pc vs. Sw values for the whole reservoir from October 1976 until December2020. MB21 unit own most Initial Oil in Place equal to 525*106 SM3 while MB12 has lowest IOIP equal to 2*106 SM3. Finally, the calculation of Initial Oil in Place by both volumetric and simulation methods presented good results while comparing with previous study at 2013 with discovered different around 1.5% and 0.6% respectively.

Reservoir simulation models are utilized by oil and gas companies with a purpose to develop fields. Expansions and improvements in simulation software have lessened the time to develop a model. Simulating the reservoir aims to realize fluid flow, physical, and chemical procedures happening in a hydrocarbon reservoir adequately well for the reason of improving hydrocarbon recovery under various working stipulations. Grid-orientation effects are complicated problem in numerical reservoir simulation. These influences were coming when utilized of numerical utilization mechanism to conditions characterizing physically inconstant displacement procedure. These impacts happen in an assortment simulation of inappropriate and favourable mobility ratio displacements. The current study presents a building static and dynamic model and suggests a development plan for the reservoir under study and change the orientation of the grids to examine the effects of these changes on the values of oil production rate, water cut, pressure, cumulative oil production, and recovery factor. The case studies for an Iraqi oil field which is located in the South East of Iraq. Different values of recovery factors were obtained when the orientation of the grids had been changed.

One of the most important enhanced oil recoveries methods is miscible displacement. During this method preferably access to the conditions of miscibility to improve the extraction process and the most important factor in these conditions is miscibility pressure. This study focused on establishing a suitable correlation to calculate the minimum miscibility pressure (MMP) required for injecting hydrocarbon gases into southern Iraq oil reservoir. MMPs were estimated for thirty oil samples from southern Iraqi oil fields by using modified Peng and Robinson equation of state. The obtained PVT reports properties were used for tunning the equation of state parameters by making a match between the equation of state results with experimental PVT data. The values ​​of the MMPs inputs into the statistical program to find a correlation for the value of miscibility pressure with the properties and composition of the reservoir oil and injected gas. Using a nonlinear formula, a good correlation was obtained. When comparing the present correlation with the many measured data, a superbly result of present correlation was obtained

As a reservoir is depleted due to production, pore pressure decreases leading to increased effective stress which causes a reduction in permeability, porosity, and possible pore collapse or compaction. Permeability is a key factor in tight reservoir development; therefore, understanding the loss of permeability in these reservoirs due to depletion is vital for effective reservoir management. The paper presents a case history on a tight carbonate reservoir in Iraq which demonstrates the behavior of rock permeability and porosity as a function of increasing effective stress simulating a depleting mode over given production time. The experimental results show unique models for the decline of permeability and porosity as function effective stress. This stress sensitivity is even more pronounced in cores with lower initial porosity and permeability. The pores’ size and shape, as well as mineral content provide important reasons for various functions in the stress-dependent behavior of the porous media. Additionally, mercury injection capillary pressure (MICP), thin section (TS) results, scanning electron microscope (SEM) data, and X-Ray diffraction (XRD) are incorporated to relate the microscopic controlling factor to stress sensitivity behavior of this reservoir formation. The results indicate that permeability is more sensitive to effective stress than the porosity. Different responses to the stress of similar initial permeability are discussed according to their mean hydraulic radius (MHR). Distinguished fabric signatures for the studied reservoir is identified from grouping the MHR-permeability relations, which is significant and can provide insight on the heterogeneity of a given reservoir and how it is related to pore size distribution. This grouping mode provided better data allocation than depending on other parameters such as; conventional samples’ initial petrophysical properties, pore size distribution, MHR values, reservoir stratigraphic units division, and clay content for the samples, which all failed in achieving reasonable data grouping for the tight reservoir under study. A relation of the viscous behavior (ductility/brittleness) of this tight reservoir to permeability and stress is examined.

The instant global trend towards developing tight reservoir is great; however, development can be very challenging due to stress and geomechanical properties effect in horizontal well placement and hydraulic fracturing design. Many parameters are known to be important to determine the suitable layer for locating horizontal well such as petrophysical and geomechanical properties. In the present study, permeability sensitivity to stress is also considered in the best layer selection for well placement. The permeability sensitivity to the stress of the layers was investigated using measurements of 27 core sample at different confining stress values. 1-D mechanical earth model (MEM) was built and converted to a 3-D full-field geomechanical model to reach perfect layer choice. The analysis of results has diagnosed the maximum horizontal stress direction of NE-SW as determined using both Fullbore Formation Micro Imager FMI and sonic scanner anisotropy analysis. The effect of porosity and permeability compaction as a result of stress changes while reservoir depletion is including on the reservoir simulation model. The choice of best layer and optimum design criteria for hydraulic fracturing is done in the current study using a compaction simulation model with the results of available measurements of geomechanical properties. The results of the simulation model show that the formation sensitivity to stress is an important factor for detecting a suitable layer for horizontal wells placement. The results of MEM indicate that horizontal stress difference (Δσ) and unconfined compressive strength (UCS) are the most important factors among geomechanical parameters affected the layer selection. From simulation results, it was found that 225 to 275 m fracture half-length gives a higher increment in oil production. The optimum number of fracture stages is noticed to be 8 to 10 stages after which the increment in production will reduce.