Crisman Annual Report 2009 - Harold Vance Department of ...

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Water Production Issues in the Barnett Shale Objectives The objectives of this research project were as follows: » Determine in a quantitative sense the effect of water production on gas production in gas shales. » Identify the different water producing mechanisms in the Barnett Shale and characterize them based on production data. » Determine the relationship between well location, reservoir, fracturing treatment/completion data and water production. Our focus was an analysis of data available from the Barnett Shale using descriptive statistical and virtual intelligence techniques. Approach A Barnett Shale water production dataset from approximately 11,000 completions was analyzed using conventional statistical techniques. Additionally, a water-hydrocarbon ratio and first derivative diagnostic plot technique developed elsewhere for conventional reservoirs was extended to analyze Barnett Shale water production mechanisms. In order to determine hidden structure in well and production data, self-organizing maps and the k-means algorithm were used to identify clusters in data. A competitive learning based network was used to predict the potential for continuous water production from a new well. A feed-forward neural network was used to predict average water production for wells drilled in the Denton and Parker Counties of the Barnett Shale (Fig. 1). Self organized maps K-means algorithm Competitive learning Vector quantizer Neural networks Enable us see how data are clustered Enable us determine optimum number of clusters Enable us partition dataset into class of water producers and non-water producers Prediction of average water/gas production Fig. 1. Utility of various virtual intelligence routines. Accomplishments Using conventional techniques, we conclude that for wells of the same completion type, location is more important than time of completion or hydraulic fracturing strategy. Liquid loading has the potential to affect vertical more than horizontal wells (Fig. 2). A MATLAB-based neural network tool was Flowing wellhead pressure (psia) 2500 2000 1500 1000 500 Minimum Required Flow Rate (Mcfd) vs WHP (psi) 0 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Average vertical well in Denton No Liquid Loading Minimum Required Flow Rate to prevent liquid loading (Mcfd) Fig. 2. Predictive Chart for onset of liquid loading in the Barnett Shale. (continued on next page) Liquid Loading region Average vertical well in Parker Average horizontal well in Denton CRISMAN INSTITUTE Project Information 1.2.10 Shale Gas Water Production Issues Average horizontal well in Parker Related Publications Awoleke, O.O. 2009. Analysis of Data from the Barnett Shale with Conventional Statistical and Virtual Intelligence Techniques. MS Thesis. Texas A&M U., College Station, Texas. Awoleke, O.O., Lane, R.H. Analysis of Data from the Barnett Shale Using Conventional Statistical and Virtual Intelligence Techniques. SPE Paper 127919 to be presented at the 2010 SPE International Symposium and Exhibition on Formation Damage Control, Lafayette, Louisiana, 10–12 February. Contacts Robert Lane 979.862.7654 robert.lane@pe.tamu.edu Obadare Awoleke Crisman Annual Report 2009 25
P90 P50 P10 Fig. 3. P10, P50 and P90 predictions of water production for horizontal wells drilled in the Parker County of the Barnett Shale. developed to predict average water production for Barnett Shale wells in Denton and Parker Counties (Fig. 3). The average prediction error for the tool varied between 10-26%, depending on well type and location. Significance Results from this work can be utilized to mitigate risk of water problems in new Barnett Shale wells and predict water issues in other shale plays. Engineers are provided a tool to predict potential for water production in new wells. The methodology used to develop this tool can be used to solve similar challenges in new and existing shale plays. 26 Crisman Annual Report 2009
Page 1 and 2: Harold Vance Department of Petroleu
Page 3 and 4: Issue 3, February 2010 Stephen A. H
Page 5 and 6: Combustion Assisted Gravity Drainag
Page 7 and 8: 6 Crisman Annual Report 2009
Page 9 and 10: Summary The Crisman Institute has t
Page 11 and 12: Membership History The Crisman Inst
Page 13 and 14: 12 Crisman Annual Report 2009
Page 15 and 16: An Advisory System for Selecting Dr
Page 17 and 18: A procedure to measure the viscosit
Page 19 and 20: PRISE - Petroleum Resource Investig
Page 21 and 22: Gas Shales Simulation and Productio
Page 23 and 24: Characterization of Rock Transport
Page 25: An Analytical Approach to Model Sha
Page 29 and 30: Density distribution from heat tran
Page 31 and 32: Experimental and Simulation Modelin
Page 33 and 34: Fig. 1. Set up of displacement appa
Page 35 and 36: Study of Solvent-Based Emulsion Inj
Page 37 and 38: Investigation of Hybrid Steam-Solve
Page 39 and 40: Experimental Studies of Steam Injec
Page 41 and 42: Combustion Assisted Gravity Drainag
Page 43 and 44: Well Spacing and Infill Drilling in
Page 45 and 46: Experimental and Numerical Simulati
Page 47 and 48: Enhanced Oil Recovery of Viscous Oi
Page 49 and 50: Alternate Power and Energy Storage/
Page 51 and 52: Propagation of Induced Hydraulic Fr
Page 53 and 54: » Use forward modeling of wellbore
Page 55 and 56: Decision Matrix for Liquid Loading
Page 57 and 58: fractions involved, a detailed sens
Page 59 and 60: Transient Multiphase Sand Transport
Page 61 and 62: Carbonate Heterogeneity and Acid Fr
Page 63 and 64: Fracture Aperture Variation Caused
Page 65 and 66: that contained 12 wt% HCl showed th
Page 67 and 68: Evaluation of Polymer-Based In-Situ
Page 69 and 70: Modeling of Discrete Fracture Netwo
Page 71 and 72: Thermo-Poroelastic Finite Element A
Page 73 and 74: Measurement and Correlation of Gas
Page 75 and 76: The falling body viscometer is sele
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Fracture permeability (md) 12 10 8
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CO 2 Mobility Control using Cross-L
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(a) Standard EnKF for permeability
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Aquifer Management for CO 2 Sequest
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Bibliography List of Theses and Dis
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» Florence, Francois; Validation/E
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» Diyashev, Ildar; Problems of Flu
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» Freeman, C.M., Ilk, D., Moridis,
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and Catalyst. Paper presented at th
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Exhibition, San Antonio, Texas, 24-
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