Application of Neural Network in the Identification of the Cumulative Production from AB unit in Main pays Reservoir of South Rumaila Oil Field.

Increasing oil production from a reservoir can be achieved by decreasing the distance between the injector and the producer through a process known as infill drilling, which involves a pattern water flood. The main objective of this study is to provide a comprehensive overview of the optimal infill well location and the research and applications available to enhance the oil recovery factor, leading to increased economic profits. one effective empirical approach used in this study is based on decline curve analysis, which analyzes the production history of the well to determine the final economic recovery. Additionally, a numerical method that combines numerical simulation and optimization techniques has been proven to be successful in determining optimal infill drilling locations. The research results show that the volumetric computation of oil in place is a useful method for estimating the number of infill wells needed, but it does not consider heterogeneity and continuity. On the other hand, the numerical simulation and optimization techniques can quantify the remaining mobile oil post-infill drilling and establish optimal pattern configurations for maximum recovery at their centers.

Section: Infill Well Placement Determination and Optimizationmentioning

confidence: 99%

Comparison Different Techniques of Optimum Location for Infill Well Drilling

Al-adliy,

Al-mahdawi,

Mohammed

et al. 2024

“…This field is near the border with Kuwait and it is recognized as one of the largest oil fields globally [13]. It is approximately located 50 kilometers west of Basra and 30 kilometers west of Zubair oilfield [14]. It covers 1,600 square kilometers, roughly 80 km in the north-south, and 20 km in the west-east of the West-Qurna oilfield.…”

Section: -Introductionmentioning

confidence: 99%

Analysis of Surge and Swab ECD of Herschel Bulkley Fluids in Rumaila Iraqi Oil Field

Salih,

Hadi,

Al Saba

2024

Surge and swab pressures are frequently produced during various stages of well construction, including casing running and tripping operations. Managing downhole pressure within the mud window is crucial for mitigating the risks associated with drilling operations including wellbore failure, lost circulation, kicks, and well control issues. The primary objectives of this study are to emphasize the theoretical foundation of surge and swab pressures, forecast the optimum pipe and casing tripping speeds, as well as identify the changes in surge and swab pressures (i.e., equivalent circulating density-ECD) for both open-ended and close-ended drill strings. To achieve these goals, a steady state surge and swab model was used to simulate a case study in the Rumaila oil field, located in Southern Iraq, by utilizing landmark-well plan software. The results of this study support the evidence that the string trip speed plays a substantial role in controlling the swab and surge pressures. It was found that pulling out the 5" drill string from the 12 1/4" open hole section drilled with a 9.51 ppg water-based mud at a speed of 10 sec/stand resulted in a swab ECD below the formation pore pressure against all formations, thus resulting in a kick. Moreover, it was found that the annular clearance had a significant impact on the surge and swab ECD whereas the surge ECD at the bit was bigger than that obtained at the previous hole casing shoe. For example, in our case study pulling speeds ranging from 10-190 sec/stand for the 9 5/8" casing could cause the swab ECD to be below the formation pore pressure gradient at total depth (TD), which is 9.23 ppg. While it was safe to run the same casing through the same interval within 55-190 sec/stand. Furthermore, the results emphasized high trip speeds ranging between 10-30 sec/stand, where for close-ended drill strings, greater surge ECD was observed compared to the open-ended ones. The surge ECD of a 5" close-ended drill string at 30 sec/stand (60 m/min) at bit was 9.92 ppg, while an open-ended string at the same speed was 9.9 ppg.

“…To meet the demand for evaluating and developing reservoirs, it may be possible to predict their performance more precisely by using comprehensive and complicated full-field reservoir models, which have become essential. In contrast to the substantial capital expenditures necessary for reservoir development, the increased knowledge and confidence in the information produced from sophisticated field-scale simulation helps the decision-making process be more reliable [2]. The reservoir model validation is the most difficult step since it requires an understanding of geoscience and reservoir engineering [3].…”

Section: -Introductionmentioning

confidence: 99%

Calibrating the Reservoir Model of the Garraf Oil Field

Abdulredha,

Al-jwad

2023

History matching is a significant stage in reservoir modeling for evaluating past reservoir performance and predicting future behavior. This paper is primarily focused on the calibration of the dynamic reservoir model for the Meshrif formation, which is the main reservoir in the Garraf oilfield. A full-field reservoir model with 110 producing wells is constructed using a comprehensive dataset that includes geological, pressure-volume-temperature (PVT), and rock property information. The resulting 3D geologic model provides detailed information on water saturation, permeability, porosity, and net thickness to gross thickness for each grid cell, and forms the basis for constructing the dynamic reservoir model. The dynamic reservoir model integrates a variety of inputs, including well position and trajectory, well completion data, initial reservoir condition, and daily production/injection rates. The validation process involves comparing the original oil reserve derived from the geological model with the one obtained from the dynamic reservoir model. To achieve an accurate history matching, the calibration process has been performed by aligning observed data with simulation results. This involves focusing on production/injection data for each well and pressure measurements for selected wells. Notably, horizontal permeability is identified as a critical parameter in this study, which is adjusted iteratively to achieve a robust match for individual wells and the entire field. Thus, Successful calibration facilitates the subsequent stage and future scenarios allowing for the exploration of different conditions to predict the performance of the Garraf oilfield. This comprehensive approach improves the reliability of reservoir predictions, facilitating well-informed decision-making in reservoir management.