Multistage Acid Fracture Effectiveness in Gas Production in the Carbonate Reservoir, Saudi Arabia - Study and Analysis of Field Examples

Author(s):  
Ashraf Islam ◽  
Zillur Rahim ◽  
Hamoud A. Al-Anazi
Author(s):  
A. Chaterine

This study accommodates subsurface uncertainties analysis and quantifies the effects on surface production volume to propose the optimal future field development. The problem of well productivity is sometimes only viewed from the surface components themselves, where in fact the subsurface component often has a significant effect on these production figures. In order to track the relationship between surface and subsurface, a model that integrates both must be created. The methods covered integrated asset modeling, probability forecasting, uncertainty quantification, sensitivity analysis, and optimization forecast. Subsurface uncertainties examined were : reservoir closure, regional segmentation, fluid contact, and SCAL properties. As the Integrated Asset Modeling is successfully conducted and a matched model is obtained for the gas-producing carbonate reservoir, highlights of the method are the following: 1) Up to ± 75% uncertainty range of reservoir parameters yields various production forecasting scenario using BHP control with the best case obtained is 335 BSCF of gas production and 254.4 MSTB of oil production, 2) SCAL properties and pseudo-faults are the most sensitive subsurface uncertainty that gives major impact to the production scheme, 3) EOS modeling and rock compressibility modeling must be evaluated seriously as those contribute significantly to condensate production and the field’s revenue, and 4) a proposed optimum production scenario for future development of the field with 151.6 BSCF gas and 414.4 MSTB oil that yields a total NPV of 218.7 MMUSD. The approach and methods implemented has been proven to result in more accurate production forecast and reduce the project cost as the effect of uncertainty reduction.


2007 ◽  
Author(s):  
Abdullah Abdulrahman Al-Fawwaz ◽  
Nedhal Mohamed Al-Musharfi ◽  
Parvez Jamil Butt ◽  
Abdul Fareed

2021 ◽  
Author(s):  
Ruijie Huang ◽  
Chenji Wei ◽  
Baohua Wang ◽  
Baozhu Li ◽  
Jian Yang ◽  
...  

Abstract Compared with conventional reservoir, the development efficiency of the carbonate reservoir is lower, because of the strong heterogeneity and complicated reservoir structure. How to accurately and quantitatively analyze development performance is critical to understand challenges faced, and to propose optimization plans to improve recovery. In the study, we develop a workflow to evaluate similarities and difference of well performance based on Machine Learning methods. A comprehensive Machine Learning evaluation approach for well performance is established by utilizing Principal Component Analysis (PCA) in combination with K-Means clustering. The multidimensional dataset used for analysis consists of over 15 years dynamic surveillance data of producers and static geology parameters of formation, such as oil/water/gas production, GOR, water cut (WC), porosity, permeability, thickness, and depth. This approach divides multidimensional data into several clusters by PCA and K-Means, and quantitatively evaluate the well performance based on clustering results. The approach is successfully developed to visualize (dis)similarities among dynamic and static data of heterogeneous carbonate reservoir, the optimal number of clusters of 27-dimension data is 4. This method provides a systematic framework for visually and quantitatively analyzing and evaluating the development performance of production wells. Reservoir engineers can efficiently propose targeted optimization measures based on the analysis results. This paper offers a reference case for well performance clustering and quantitative analysis and proposing optimization plans that will help engineers make better decision in similar situation.


2021 ◽  
Author(s):  
Frank Figueroa ◽  
Gustavo Mejías ◽  
José Frías ◽  
Bonifacio Brito ◽  
Diana Velázquez ◽  
...  

Abstract Enhanced hydrocarbon production in a high-pressure/high-temperature (HP/HT) carbonate reservoir, involves generating highly conductive channels using efficient diversion techniques and custom-designed acid-based fluid systems. Advanced stimulation design includes injection of different reactive fluids, which involves challenges associated with controlling fluid leak-off, implementing optimal diversion techniques, controlling acid reaction rates to withstand high-temperature conditions, and designing appropriate pumping schedules to increase well productivity and sustainability of its production through efficient acid etching and uniform fluid distribution in the pay zone. Laboratory tests such as rock mineralogy, acid etching on core samples and solubility tests on formation cuttings were performed to confirm rock dissolving capability, and to identify stimulation fluids that could generate optimal fracture lengths and maximus etching in the zone of interest while corrosion test was run to ensure corrosion control at HT conditions. After analyzing laboratory tests results, acid fluid systems were selected together with a self-crosslinking acid system for its diversion properties. In addition, customized pumping schedule was constructed using acid fracturing and diverting simulators and based on optimal conductivity/productivity results fluid stages number and sequence, flow rates and acid volumes were selected. The engineered acid treatment generated a network of conductive fractures that resulted in a significant improvement over initial production rate. Diverting agent efficiency was observed during pumping treatment by a 1,300 psi increase in surface pressures when the diverting agent entered the formation. Oil production increased from 648.7 to 3105.89 BPD, and gas production increased from 4.9 to 26.92 MMSCFD. This success results demonstrates that engineering design coupled with laboratory tailor fluids designs, integrated with a flawless execution, are the key to a successful stimulation. This paper describes the details of acidizing technique, treatment design and lessons learned during execution and results.


2008 ◽  
Author(s):  
Abdullah M. Al-Dhafeeri ◽  
Hisham A. Nasr-El-Din ◽  
Abdullah M. Al-Harith

2008 ◽  
Author(s):  
Sezgin Tayyar Daltaban ◽  
A. Miguel Lozada ◽  
Antonio Villavicencio Pina ◽  
F. Marcos Torres

2008 ◽  
Author(s):  
Abdullah M. Al-Dhafeeri ◽  
Hisham A. Nasr-El-Din ◽  
Hassan Khalifah Al-Mubarak ◽  
J. Al-Ghamdi

2005 ◽  
Author(s):  
D.A. Al-Shehri ◽  
A.S. Rabaa ◽  
J.J. Duenas ◽  
V. Ramanathan

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