When the first frac pack was performed in the Gulf of Mexico (GOM) over a decade ago, very little was known about the effects this form of sand control would have on the intended formation. Even less was known about how to optimize the treatment to get the most benefit for the formation. Since that time, the sand control community has learned a great deal about the effects and benefits of frac packing various unconsolidated formations throughout the world. However, most of the knowledge and design criteria have been housed within the minds of individuals and cannot be looked at as a whole to find trends and fine tune the design methods currently being used. Another complicating factor is the number of frac models being used within the industry with varying degrees of complexity. Therefore, even though thousands of frac packs have been performed globally, frac-pack redesign methods are still subjective and differ from individual to individual and model to model. The recent creation of a database that houses selected formation evaluation test (FET) and frac data, along with model-specific parameters, allows full-scale analysis of a large number of jobs pumped in the Gulf of Mexico. With a consistent analysis procedure in place, the database, populated with numerous treatments by engineers working throughout the GOM, can be analyzed objectively. The data contained in this database include rock mechanics, net pressures, pumping trend data, tip screenout (TSO) times, etc. This paper explains the methodology and discusses the results of the database analysis, using case studies to determine the best method for analysis of the jobs. Crossplots show the correlation between TSO prediction and actual events and suggests recommendations for more successful future design work. This paper is meant to give up-to-date guidelines to help design better frac packs. Introduction Within the sand control community, the ability of an engineer to redesign a frac pack from data generated during the minifrac can sometimes be considered more art than science. Often the engineer whose job it is to formulate the frac pack treatment will use several different methods to arrive at a solution deemed most correct. Many hours are dedicated to determining the proper design for a frac-pack treatment. While often the results cannot be argued, it is unwise and possibly a waste of time to reinvent the wheel for every job. Rather, it should be the goal of the sand control and frac-pack communities to develop a design method that can determine the most important parameters necessary to complete the job. This method would be easily repeatable and could be used throughout the GOM and possibly in other high-permeability, unconsolidated regions of the world. The purpose of this paper is to solve the problem previously described. The goal of the project was to accurately predict the TSO event such that the fracture geometry could be better understood. In fracture theory, the TSO[1] is the point at which there is no longer any propagation of the fracture length. Most fracture models treat this as the time at which the first grain of sand is exposed to the tip of the fracture, ceasing any further growth and allowing net pressure to accumulate and build width throughout the length of the fracture. The creation of a standard reliable method for predicting the onset of the TSO event would enable engineers involved in designing frac-pack operations to become more aligned in their procedures, as well as provide more accurate results. Knowing which "knobs" within the fracture model should be manipulated in order to get the most accurate results would be invaluable. This would allow for much quicker analysis of the data accumulated from the minifrac thereby saving expensive rig time. In addition, should multiple engineers be analyzing the data, a single reliable method would allow a much more concrete determination of any issues because everyone should see very similar results. There have been many efforts to do this in the past.[2] This paper presents the methodology behind developing a database system to track frac-pack treatment data, what data was deemed necessary to a reliable model, and the procedure for procuring that information from various fracture treatments. Then, case studies are presented that prove that the model, populated following the recommended procedure, accurately predicts the TSO event in various situations.

When the first frac pack was performed in the Gulf of Mexico (GOM) over a decade ago, very little was known about the effects this form of sand control would have on the intended formation. Even less was known about how to optimize the treatment to obtain the most benefit for the formation. Since that time, the sand control community has learned a great deal about the effects and benefits of frac-packing various unconsolidated formations throughout the world. However, most of the knowledge and design criteria have remained housed within the minds of individuals and cannot be looked at as a whole to find trends and fine-tune the design methods currently being used. Another complicating factor is the number of frac models of varying degrees of complexity being used within the industry. Therefore, even though thousands of frac packs have been performed globally, frac-pack redesign methods are still subjective and differ from individual to individual and from model to model.The recent creation of a database that houses selected formation evaluation test (FET) and frac data along with model-specific parameters allows full-scale analysis of a large number of jobs pumped in the Gulf of Mexico (GOM). With a consistent analysis procedure in place, the database, populated with numerous treatments by engineers working throughout the GOM, can be analyzed objectively. The data contained in this database include rock mechanics, net pressures, pumping trend data, tip screenout (TSO) times, and other variables.This paper explains the methodology and discusses the results of the database analysis, using case studies to determine the best method for analysis of the jobs. Crossplots show the correlation between TSO prediction and actual events and suggest recommendations for more successful design work in the future. This paper is meant to give up-to-date guidelines for designing better frac packs.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractWhen the first frac pack was performed in the Gulf of Mexico (GOM) over a decade ago, very little was known about the effects this form of sand control would have on the intended formation. Even less was known about how to optimize the treatment to get the most benefit for the formation. Since that time, the sand control community has learned a great deal about the effects and benefits of frac packing various unconsolidated formations throughout the world. However, most of the knowledge and design criteria have been housed within the minds of individuals and cannot be looked at as a whole to find trends and fine tune the design methods currently being used. Another complicating factor is the number of frac models being used within the industry with varying degrees of complexity. Therefore, even though thousands of frac packs have been performed globally, fracpack redesign methods are still subjective and differ from individual to individual and model to model.The recent creation of a database that houses selected formation evaluation test (FET) and frac data, along with model-specific parameters, allows full-scale analysis of a large number of jobs pumped in the Gulf of Mexico. With a consistent analysis procedure in place, the database, populated with numerous treatments by engineers working throughout the GOM, can be analyzed objectively. The data contained in this database include rock mechanics, net pressures, pumping trend data, tip screenout (TSO) times, etc.This paper explains the methodology and discusses the results of the database analysis, using case studies to determine the best method for analysis of the jobs. Crossplots show the correlation between TSO prediction and actual events and suggests recommendations for more successful future design work. This paper is meant to give up-to-date guidelines to help design better frac packs.