Practical Production Data Analysis for the Appalachian Basin
- J.H. Frantz Jr. (_) | J.P. Spivey (_) | G.W. Voneiff (_) | H. Jacot (_)
- Document ID
- Society of Petroleum Engineers
- SPE Eastern Regional Meeting, 23-25 October, Columbus. Ohio
- Publication Date
- Document Type
- Conference Paper
- 1996. Society of Petroleum Engineers
- 4.1.2 Separation and Treating, 5.7 Reserves Evaluation, 5.6.1 Open hole/cased hole log analysis, 5.8.6 Naturally Fractured Reservoir, 5.5 Reservoir Simulation, 1.6 Drilling Operations, 5.8.2 Shale Gas, 4.3.4 Scale, 5.4.2 Gas Injection Methods, 5.2.1 Phase Behavior and PVT Measurements, 4.1.5 Processing Equipment, 3.1.5 Plunger lift, 5.1 Reservoir Characterisation, 5.5.8 History Matching, 4.1.6 Compressors, Engines and Turbines, 5.6.3 Pressure Transient Testing, 5.6.4 Drillstem/Well Testing, 2.4.3 Sand/Solids Control, 3.2.3 Hydraulic Fracturing Design, Implementation and Optimisation, 5.6.9 Production Forecasting, 3.2.4 Acidising
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J.H. Frantz, Jr., J.P. Spivey, G.W. Voneiff, and H. Jacot
This paper presents several production data analysis case histories from wells in the Appalachian Basin. The primary purpose of this work is to illustrate the practical application of advanced production data analysis methods in Appalachian reservoirs. Production data provide important information about reservoir quality and volume and the stimulation effectiveness. The analysis results can provide estimates for permeability-thickness product, skin factor or fracture half-length, gas in place, and drainage area. Pressure transient information can also be integrated with production data analysis to further characterize the reservoir.
Practical applications of production data analysis results include estimating short- and long-term production rates, estimating reserves, designing/evaluating stimulation (and restimulation) treatments, predicting and evaluating production increases from changes in flowing well pressure (plunger-lift and compressor installations), determining infill well potential and optimal well spacing, and identifying natural fracture and/or layered behavior. We will show an example of several applications from the Rose Run, Beekmantown, Clinton/Medina, Berea and Queenston reservoirs. New type curves were also used in this work to analyze difficult datasets and to provide a starting point for more sophisticated history-matching methods. The final portion of this paper will include recommendations for field data collection and database utilization.
Many Appalachian Basin operators collect detailed information on their wells' production histories. This information can be analyzed to better understand the reservoir and make prudent operating decisions. The well data collected typically include daily or weekly gas, water, and condensate volumes, tubing, casing, and line pressures, days on line, choke settings, plunger-lift cycle information, fluid levels, and occasional shut-in pressures.
Some operators also perform pressure transient testing occasionally to evaluate reservoir quality, wellbore damage or stimulation, and reservoir pressure. In most cases for Appalachian Basin reservoirs, production data can be analyzed to provide similar information and investigates more reservoir than short-term pressure transient tests. Production data often show reservoir characteristics such as layered- or naturally-fractured behavior that are not evident in pressure transient testing. A combination of production data and pressure transient analysis can be effective tools to evaluate reservoir behavior. In this paper, we discuss several advanced production data analysis techniques and their application in Appalachian Basin wells.
There are at least five objectives which may be achieved by production data analysis, pressure transient analysis, and other means of formation evaluation. These are degree of stimulation, formation permeability, current average drainage area pressure, original gas in place (OGIP) or drainage area, and reserves. Since each analysis method typically investigates the reservoir at a different length scale, some analysis methods are more useful for achieving a given objective than are other methods.
Production Data Analysis. There are a number of commonly used methods for analyzing production data, including conventional decline curve analysis, advanced decline curve analysis, automatic history matching, and numerical reservoir simulation.
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