Kashy Aminian

A New Approach to Predict Bit Life Based on Tooth or Bearing Failures

This paper presents a new methodology to predict the wear for three-cone bits under varying operating conditions. In this approach, six variables (weight on bit, rotary speed, pump rate, formation hardness, bit type, and torque) were studied over a range of values. A simulator was used to generate drlling data to eliminate arrors coherent to field measurements. The data generated was used to establish the relationship between complex patterns. A three-layer artificial neural network was designed and trained with measured data. This method incorporates computational intelligence to define the relationship between the variables. Further, it can be used to estimate the rate of penetration and formation characteristics. The new model was successful in predicting the condition of the bit. In this study, the value of 0.997 was obtained by the model as the correlation coefficient between the predicted and measured bearing wear and tooth wear values. The validity of the model was demonstrated with data from an existing field. Introduction There are numerous technological advances made in the design and manufacture of drilling bits. The demand to drill faster and physically for a longer period is the driving force behind these developments. Consequently, the trip times and the time spent to drill a well are reduced. This in turn yields a cost effective drilling operation. The need to understand the bit behavior has been long recognizedl-3. Several investigators conducted research to estimate the bit condition based on operational parameters and measured data from offset wells4-9.The models developed are based on assumptions that limit their applicability. Neural Networks. Recently, neural networks successfully applied in different areas of petroleum engineeringlO. The capability to ident.@ complex relationships is well suited to solve problems inherent to oil and natural gas operations. When sufllcient data exists, the use of neural networks are demonstrated in several areas such as multi-phase pipe flow’“12, reservoir characterization13”4, production15’16, and drilling17’18. Especially the drilling operation provides a unique challenge due to..the number of_vmjables involved. These parameters range from unknown formation characteristics and down hole conditions to surface operating conditions. A neural network to predict the rate of penetration values at a well based on recorded data was presented earlier18. In this study, a new neural network was designed and used to predict successfully the bit wear and life. Approach Anew methodolo~ is introduced to predict the bit tooth and bit bearing wear while drilling. In this study, a neural network model was selected to investigate a complex drilling problem. The study consists of simulated and field measured data sets. Approximately 8000 set of measurements were recorded using the rig floor simulator available in the departmental facilities. The use of simulated data provided additional information such as bit tooth and bearing wear that were not recorded in the field during the drilling operation. The bit condition in the field is determined only after it is pulled. The data recorded using the rig floor simulator consisted of bit tooth and bearing wear values as a function of time. The range of data used in this study are given in Table 1 where the formation drillability varied between 30 and 75 with smaller values representing harder formations. Similarly, the formation abrasiveness values represent an increasing abrasiveness from one to eight. The wellbore con.tlgurat.ionsand other operational parameters were kept constant during rig floor simulator runs. Several neural networks were developed to predict the bit tooth and bearing wear values. All networks used a typical three-layer feed-forward back propagation similar to Figure 1. The neural network models used in this study were consisted of 80 hidden neurons, nine or ten input parameters, and one or two output parameters. First and second neural networks were designed to predict bit tooth wear and bit bearing wear, respec-

Evaluation of Coalbed Methane Reservoirs

Coal, unlike conventional gas reservoirs, is both the reservoir rock and the source rock for methane. While much of the gas generated during coalification migrated out of the coal seam, significant quantities remain in coal that can be produced from a seam by understanding and evaluating the unique properties of coal. The CBM characteristics and testing techniques to determine key reservoir parameters needed for developing a CBM prospect will be discussed in the following sections.

Estimation of Skin Factor by Using Pressure Transient Testing Results of a Single Rate Well Test

Estimation of Skin Factor by Using Pressure Transient Testing Results of a Single Rate Well Test

The Impact of Stress on Propped Fracture Conductivity and Gas Recovery in Marcellus Shale

It is commonly observed that the production rates from unconventional reservoirs decline rapidly as compared to conventional reservoirs. The net stress increases with the production because the pore (fluid) pressure decreases while the overburden pressure remains constant. This leads to the fracture compaction and conductivity impairment due to proppant embedment. Even though advances in technology have unlocked considerable reserves of hydrocarbon, the impact of the net stress changes on proppant conductivity, i.e. stress-dependent propped fracture conductivity, is not well understood. The objective of this study is to investigate the impact of the net stress propped fracture conductivity from the horizontal wells with multiple hydraulic fractures completed in Marcellus Shale. A commercial reservoir simulator was used to develop the base model for a Marcellus Shale horizontal well. The model incorporated various storage and production mechanisms inherent in Shales i.e. matrix, natural fracture, and gas adsorption as well as the hydraulic fracture properties (half-length and conductivity). The core, log, completion, stimulation, and production data from wells located at the Marcellus Shale Energy and Environment Laboratory (MSEEL) were utilized to generate the formation and completion properties for the simulation model. MSEEL is a Marcellus Shale dedicated field laboratory and a research collaboration between West Virginia University, Ohio State University, The National Energy Technology Laboratory, and Northeast Natural Energy. Precision laboratory equipment was utilized to determine rock petrophysical properties such as permeability and porosity. Additionally, the natural fracture closure stress values were determined by an innovative experimental technique using core plug samples. The relation between fracture conductivity and the net stress were obtained from published studies (SPE 181867) on core plugs collected from Marcellus shale at two different locations. This relation was incorporated in the model to investigate the geomechanical impact of hydraulic fracture on the gas production. The model was used to perform a number of parametric studies to investigate geomechanical effects for fracture conductivity on gas recovery from Marcellus shale. The production data from two horizontal wells at the MSEEL site, were utilized for production history matching both with and without geomechanical effects. The inclusion of the geomechanical effect in the model improved the predictions particularly at the early stages of the production. Simulation results show geomechanical effects of fracture conductivity on gas production performance for Elimsport and Allenwood

The Impact of the Hydraulic Fracture Properties on the Gas Recovery from Marcellus Shale

Marcellus Shale, a Devonian black shale, spans the majority of the Appalachian Basin from New York through Pennsylvania, West Virginia and also extends into Ohio and Maryland (Bartuska, et al. 2012). The unconventional gas reservoir is a term commonly used to refer to ultra-low permeability formations that produces mainly dry natural gas and is not able to produce an economic flow rate without stimulation treatments. The natural gas in the Marcellus Shale is produced most efficiently through horizontal wells with multiple hydraulic fracturing stimulation treatments. Even though advances in technology have unlocked considerable reserves of hydrocarbon, the long-term production behavior of the horizontal wells with multiple hydraulic fractures is not well understood. This paper provides the results of parametric studies to investigate the impact of the hydraulic fracture properties and more specifically the impact of non-uniform fracture half-length, on the gas recovery from Marcellus Shale. The purpose of this study is to evaluate the long-term production performance of horizontal wells with multiple hydraulic fractures completed in Marcellus Shale. A commercial reservoir simulator was used to develop the base model which incorporated the storage and production mechanisms inherent in shales. The core, log, completion, stimulation, and production data obtained from wells located at the Marcellus Shale Energy and Environment Laboratory (MSEEL) were utilized to generate the simulation model. MSEEL is a research collaboration between West Virginia University, Ohio State University, The Natural Energy Technology Laboratory, and Northeast Natural Energy. MSEEL aims to achieve a better understanding of the unconventional shale resources through application of advanced technology in drilling, completion, reservoir characterization, production and monitoring of horizontal wells. Furthermore, fracture properties (fracture half-length, fracture width and fracture conductivity) were obtained by using commercial software. Precision laboratory equipment was utilized to determine the shale properties from the core samples. Field production data from two original horizontal Marcellus Shale gas wells at MSEEL site were utilized for history matching to establish the missing shale parameters. History matching was initially performed using production data for two years from one the horizontal wells. The matched model was then used to predict the production for the following two years to confirm the accuracy and reliability of the model. In addition, the base model was used to predict the second horizontal well production which provided reliable results. Finally, a number of parametric studies were performed with the model to investigate the impact of the hydraulic fracture properties and non-uniform fracture half-length, on the recovery.

Enhanced liquid recovery by carbon dioxide sequestration in gas/condensate reservoirs

CO2 sequestration in a depleted gas/condensate reservoir could be a viable option due to the economic benefits associated with the enhanced liquid recovery. According to previous laboratory investigations, CO2 may be superior to methane (CH4) or nitrogen (N2) for enhanced condensate recovery from the depleted gas/condensate reservoirs. However, the impact of CO2 distribution(and the associated mixing with the reservoir fluid) on liquid recovery from the gas/condensate has not yet been investigated. In this study, a compositional reservoir simulation was used to investigate the impact of the reservoir characteristics on the CO2 distribution and the interactions with the hydrocarbons in gas/condensate reservoirs. The results indicate that CO2 sequestration is able to significantly improve the liquid recovery even when severe heterogeneities are present. The liquid recovery not only results in economic benefits but also provides additional pore space for CO2 storage.