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Abstract Using the right drilling fluid with optimal rheology and filtration properties is one of the most important factors in successful drilling and completion operations. Designing the right drilling fluid depends on a variety of factors viz. formation lithology, wellbore geometry, temperature, pressure, and drilling objectives. To the best of the author's knowledge there is no standard drilling fluid advisory system to aid drilling engineers and scientists to formulate effective drilling fluids systems for the entire well sections. The paper describes a drilling fluid advisory system based on Artificial Bayesian Intelligence. The advisory system includes a Bayesian decision network (BDN) model that receives inputs and outputs recommendations based on Bayesian probability determinations. This advisory system has been designed to aid drilling engineers when designing drilling fluids for their operations. This paper describes a module that was created in this advisory system. This module was created based on several inputs viz. well geometry (vertical and horizontal), temperature, pressure, productivity. To create the drilling fluids module within the advisory system, a number of drilling fluid specialists/experts were interviewed to gather the information required to determine the best practices as a function of the above inputs. These best practices were then used to build decision trees that would allow the user to take an elementary data set and end up with a decision that honors the best practices. The designing process of this advisory system also included a number of standard lab tests that start from quality assurance, initial designing and finally using field samples to confirm the success of the application. The study also discusses several field cases that validate the drilling fluids advisory system. The novel drilling fluid advisory system based on Artificial Bayesian Intelligence has been designed to aid drilling engineers and scientists to formulate effective drilling fluids systems for the entire well sections.
Saleh, Ibrahim Abdul-Salam (University of Technology / Petroleum Technology Department) | Mahdi, Bashar Saadoon (University of Technology / Computer Sciences Department) | Al-Jawad, Mohammed Saleh (University of Technology / Petroleum Technology Department)
Abstract Basrah oil fields contain many unresolved drilling problems, some of which are treated with difficulty, inefficiency, and sometimes leading to a more complex problem. These inefficient problems handling procedures lead to a longer Non-Productive Time (NPT). This lack in efficiency often comes from inadequate preparation, or the slow decision making in the detection of the drilling problems. The main objective of this study is to provide the optimum solutions for the drilling problems in Basrah oil fields on smartphones to achieve credible and quick treatments anywhere on the field. Tracing of the problems, the gathering process of the field data, and the analysis of the field procedures to treat a problem, all of which were difficulties and challenges faced. Field data deficiency was confronted in many stages. Throughout this paper, strategies of treatment procedures for the problems that could be encountered while drilling in Basra oil fields are discussed such as Dammam formation's losses, Tanuma's shale instability, Mishrif's special treatments so as not to damage the reservoir, and many others. Discussion of every formation that is drilled from the surface to Mishrif formation will be carried out with the explanation of the problems that was faced in offset wells, in addition to the problems that have a possibility to happen in each formation. The treatments for each problem were based on past field experience and standardized procedures. All of the formations, the problems, and the treatments are constructed in an application called Problems Detector 1.0 (PD) that functions on smartphones that obtains a familiar user interface and can be used anywhere on the field. Two advanced programming techniques are used to construct PD using an Object Oriented Programming language (OOP) that is java, they are the classify algorithm and a well secured database used to enhance the application's capabilities to detect problems and secure the wellbeing of the data that are mounted in PD, respectively. As a result, a full database of the drilling problems in Basrah oil fields has been constructed. All the problems that could be tackled while drilling with the possibility of their occurrence, the causes of these problems, the indications of the problems on the rig, and the treatment of each problem were all parts of the database set in PD. Smart phones showed very high efficiency and speed in determining the problems and presenting the solution which can be used on field by the drilling engineer and/or the driller, therefore; the presentation of smartphones to the petroleum industry has proven its importance and value.
Skalle, Pål (Norwegian University of Science and Technology, Department of Petroleum Engineering and Applied Geophysics) | Aamodt, Agnar (Norwegian University of Science and Technology, Department of Computer and Information Science) | Gundersen, Odd Erik (VerdandeTechnology A/S)
Summary When a diagnosis of a problem is known, the problem can usually be solved efficiently. This paper presents a method that helps reveal the most probable cause of a drilling-process failure immediately after occurrence. Normally, it takes some time to investigate and evaluate all available information before the correct cause can be determined. The method presented is targeted at reducing this time and at the same time improving the quality of the interpretation. The method relies on input parameters from the ongoing drilling process, parameters that behave irregularly and are referred to as symptoms or errors when the irregularity is severe. Recognized symptoms are used as input parameters in a knowledge-modeling method that relates symptoms to failures. The method was verified on the basis of historical drilling data, and its ability to point out the correct causes with high probability was demonstrated. Field testing the method is yet to be performed.
Abstract Texas A&M University recently has established a new method to develop a drilling expert system that can be used as a training tool for young engineers or as a consultation system in various drilling engineering concepts such as drilling and completion fluids, cementing, completion, and underbalanced drilling practices. To the best of the authors knowledge there is no standards developed to aid drilling engineers and scientists to formulate effective drilling fluids systems for the entire well sections. The objective of this paper is to set a module that should aid drilling engineers when designing drilling fluids. A module was created based on several inputs. To create this module, we interviewed experts to gather the information required to determine best practices as a function of different probabilities. Drilling fluids formulations were gathered from Saudi Arabia fields to build up this model. The Bayesian approach was found suitable for designing expert system. The model can work as a guide to aid drilling engineers and scientists to design and execute optimum drilling fluids. Using this approach to build up expert systems is more flexible than using flow charts. Updating flow charts is time consuming and require redesigning them again to be used by different experts or in different fields. Using Bayesian network allows us to update our industry practices by updating the probabilities states mentioned in this paper.
Abstract Long years of experience in the field and sometimes in the lab are required to develop drilling fluid consultants. Texas A&M University recently has established a new method to develop a drilling expert system that can be used as a training tool for young engineers or as a consultation system in various drilling engineering concepts such as drilling and completion fluids, cementing, completion, and underbalanced drilling practices. Drilling fluids are important factor in drilling and completion operations. Designing drilling fluids depend on formation lithology, temperature and pressure. To the best of the authors knowledge there is no standards developed to aid drilling engineers and scientists to formulate effective drilling fluids systems for the entire well sections. To the best of the authors' knowledge, this paper is the first study to show a systematic method to design drilling fluids for oil and gas wells. The objective of this paper is to set a module that should aid drilling engineers when designing drilling fluids. A module was created based on several inputs. To create this module, we interviewed experts to gather the information required to determine best practices as a function of different probabilities. We used these best practices to build decision trees that allow the user to take an elementary data set and end up with a decision that honors the best practices.
Abstract Emulsions have been used for many applications in the petroleum industry for many decades. Emulsified acid has been used in acid fracturing and well acidizing since 1933. A large number of fracturing treatments that used emulsified acid has been reported in the literature. Another fair number of researchers conducted lab experiments utilizing the emulsified acid. However, all of this work cannot be reproduced because of inadequate characterization of the emulsion. One essential way to characterize emulsions is by their droplet size. Various mixing modes and proportions produce emulsions with different size distributions for the dispersed phase. Those physical variations are believed to generate different properties (viscosity, stability, etc) of the emulsions. The main objective of this paper is to provide a detailed description of the droplet size distribution of emulsified acids. Methods to measure and represent the data are the core of this section. We show that coarse or fine emulsions can be produced by selecting the mode of mixing and speed of shearing. Simple mixing and low shearing produce coarse emulsions whereas atomizing and high shearing produce fine emulsions. It is also demonstrated that the droplet size and specific surface area are affected by emulsifier concentration and acid volume fraction. Average droplet size decreases with increasing emulsifier concentration. The diameter also increases with increasing acid volume fraction. The specific surface area of the droplets increases with increasing emulsifier concentration and decreases with increasing acid volume fraction. The change of droplet size has a practical impact on the stability, rheology and reactivity of emulsified acid. Good understanding and characterization of the emulsified acid by its size distribution will lead to advancements in this area. Introduction An emulsion is a mixture of two immiscible liquids. One liquid is called the dispersed phase because it forms the internal phase and the other liquid is called the continuous phase because it forms the external phase. In the emulsified acid system, a continuous liquid phase which is diesel surrounds droplets of hydrochloric acid forming acid-in-diesel emulsion. It is the practice of the petroleum industry to use a concentrated (15–28 wt%) hydrochloric acid. The emulsified acid system is stabilized by adding an emulsifier. Because emulsions are unstable and thus do not form spontaneously, the emulsifier is needed to reduce the interfacial tension between the acid and the diesel to a value that allows the two phases to mix and form one mixture. Once formed, the emulsified acid system should remain stable for a minimum time that allows it to be pumped to the formation. The emulsifier is a surface active agent (surfactant) that reduces the interfacial tension between oil (diesel) and water (acid) by adsorbing at the liquid-liquid interface.