{"id":10662,"date":"2022-09-29T07:50:22","date_gmt":"2022-09-29T07:50:22","guid":{"rendered":"https:\/\/file.currentschoolnews.com\/?post_type=product&p=10662"},"modified":"2022-09-29T10:47:08","modified_gmt":"2022-09-29T10:47:08","slug":"an-approach-to-stimulation-candidate-selection-and-optimization","status":"publish","type":"product","link":"https:\/\/pastexamquestions.com\/product\/an-approach-to-stimulation-candidate-selection-and-optimization\/","title":{"rendered":"An Approach To Stimulation Candidate Selection And Optimization"},"content":{"rendered":"

– An Approach To Stimulation Candidate Selection And Optimization –<\/strong><\/span><\/p>\n

Download An Approach To Stimulation Candidate Selection And Optimization<\/strong><\/span>. Students who are writing their projects can get this material to aid their research work.<\/span><\/span><\/p>\n

Abstract<\/strong><\/h3>\n

Well, stimulation consists of several methods used for enhancing the natural producing ability of the reservoir when the production rate declines. A detailed literature review of some of the well-published simulation models are discussed in this research.<\/p>\n

This discussion was preceded with an introduction to formation damage concepts and an overview of well stimulation methods. Production decline curve analysis is combined with economic discounting concepts to develop a model that can be used for optimizing stimulation decisions.<\/p>\n

The model is presented in the form of a non-linear programming problem subject to the constraints imposed by the production facilities, reservoir productivity, and the stimulation budget approved by management.<\/p>\n

Production data from four stimulation candidate wells, offshore Niger Delta was used to validate the model developed by setting up a maximization problem. The solution to the problem was obtained using non-linear optimization software. The result obtained was verified using Wolfram\u00a0 Research’s Mathematica 7.0<\/em>.<\/p>\n

The results show that the optimization model can be combined with stimulation treatment modules, developed from industry-wide models, to quantify stimulation benefits. C candidate wells were then ranked based on stimulation cost, payout time and stimulation benefit.<\/p>\n

Hence, the model is valid for stimulation candidate selection; and is therefore recommended for use in optimizing stimulation decisions.<\/p>\n

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Introduction<\/strong><\/h3>\n

1.1 Background of the Study<\/strong><\/p>\n

Permeability reduction in the region near the wellbore in a producing zone is referred to as \u201cdamage\u201d. The damaged region is called skin zone while the term \u201cskin effect\u201d refers to a dimensionless parameter used to quantify the extent of damage.<\/p>\n

Reduction in permeability in the near-wellbore region results in lower productivity due to increased pressure drop, hence damage is not desirable.<\/p>\n

The Composite Skin Effect<\/strong><\/p>\n

The skin effect can be obtained from a well test. It measures the extent of damage in the near-wellbore zone.<\/p>\n

The total skin effect obtained from the well test is a composite parameter which consists of skin components due to mechanical causes \u2013 a disturbance of the fluid flow streamline normal to the well, or formation damage – alteration of the natural reservoir permeability.<\/p>\n

It is very important to be able to identify the formation damage component of the skin since t his can be reduced by better operational practices, or possibly, b e removed or bypassed by stimulation treatments.<\/p>\n

Formation damage can result from many different operations such as drilling, cementing, perforating, completion\/gravel packing, production, injection, workover, stimulation, etc.<\/p>\n

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