Abstract

In a detail data mining study about 150 wells that have been completed in the Codell formation, DJ Basin, have been analyzed to identify successful practices in hydraulic fracturing. The Codell formation is a low permeability sandstone within the Wattenburg field in the DJ Basin of Colorado. Since 1997 over 1500 Codell wells have been restimulated. As part of a Gas Research Institute restimulation project 150 wells were studied to optimize candidate selection and identify successful practices.

Hydraulic fracturing is an economic way of increasing gas well productivity. Hydraulic fracturing is routinely performed on many gas wells in fields that contain hundreds of wells. During the process of hydraulically fracturing gas wells over many years, companies usually record the relevant data on methods and materials in a database. These databases usually include general information such as date of the job, Service Company performing the job, fluid type and amount, proppant type and amount, and pump rate. Sometimes more detail information may be available such as breakers, additives, amount of nitrogen, and ISIP to name a few.

These data are usually of little use in complex 3-D hydraulic fracture simulators. These models require additional and more detailed information. On the other hand, the collected data contain valuable information that can be processed using virtual intelligence tools. The process covered in this paper takes the above-mentioned data and couples it with general information from each well (things like latitude, longitude and elevation), any information available from log analysis and production data. The conclusion of the analysis is a set of successful practices that has been implemented in a particular field and recommendations on how to precede with further hydraulic fracture jobs.

In this paper the results of applying this process to about 150 Codell wells during the GRI sponsored project is presented. This process provides an important step toward constructing a comprehensive set of methods and processes for data mining, knowledge discovery, and data-knowledge fusion from data sets in oil and gas industry.

Introduction

Patina Oil and Gas has been very active in the DJ basin in recent years. They have been one of the most active operators in the United States in identifying and restimulationg tigh gas sand wells. Patina has over 3,400 producing wells in the basin, and has restimulated over 230 Niobrara/Codell completions so far. Furthermore, it is estimated that the results they are achieving in terms of incremental recoveries are up to 60% better than other operators.

Studies and analysis such as the one being presented in this paper has the potential to help operators like Patina Oil &Gas to increase their chance of success even to a higher percentage. It also has the potential to help other operators in increasing their chances of success in DJ Basin or any other locations throughout the North America. This stuy is probably one of the most comprehensive analyses of its kind ever to be performed on a set of wells in the United States.

In this technical paper the authors' intention is to introduce this new and novel methodology in its entirety and present as much of the results as the page limitations of this paper allows. Please note that due to the comprehensive nature of this methodology many of the topics cannot be discussed in much detail. It is our intention to introduce these topics in much more detail in series of upcoming technical papers.

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