A Gaussian Decomposition Method and its applications to the prediction of shale gas production

Abstract History matching is normally used to predict the gas production and guide refracturing. This can be achieved either through a mathematics-based approach such as decline curve fitting or through a physics-based approach such as reservoir simulation. When applied to the case of shale gas, both approaches are not working well. In this study, a Gaussian Decomposition Method (GDM), as an alternative approach, is developed and applied to the investigation of shale gas production. In this approach, an auto-compute program is developed and applied to a spectrum of scales from the core scale to the reservoir scale. Specific steps are as follows: (1) we use the experimental measurements to determine the initial gas content distribution; (2) we use the gas production history to decompose the evolving contributions of different gas components in a shale gas reservoir; and (3) we extend the history matching to predict the production of shale gas under similar extraction conditions. For the core scale, we use the automatically decomposed Gaussian components to illustrate the evolving contributions of different gas components including the free-phase gas in pores, the adsorbed gas and the diffused gas to the overall gas production. In the reservoir study, GDM is applied to the production data history matching and real-time prediction. Firstly, GMD is verified against a commercial software on daily, monthly and annual gas production rates. Then a group of daily and monthly field data are history matched by GDM. Finally, GDM is applied to predict the real-time gas production rate. Application results indicate: (a) the early gas production is mainly from big pores/fractures while the late production is from kerogen/clay components; (b) The period of gas production in the early stage is relatively short while the period in the late stage is long.

[1]  M. Salakhov,et al.  Resolution enhancement of composite spectra using wavelet-based derivative spectrometry. , 2005, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[3]  T. Doe,et al.  Discrete Fracture Network Simulation of Production Data from Unconventional Wells , 2014 .

[4]  Roswell H. Johnson,et al.  The Loss Ratio Method of Extrapolating Oil Well Decline Curves , 1927 .

[5]  Zhangxin Chen,et al.  Measurement of gas storage processes in shale and of the molecular diffusion coefficient in kerogen , 2014 .

[6]  Shi-Nine Yang,et al.  Automatic determination of the spread parameter in Gaussian smoothing , 1996, Pattern Recognit. Lett..

[7]  Deepankar Biswas.  Shale Gas Predictive Model (SGPM)--An Alternate Approach To Model Shale Gas Production , 2011 .

[8]  Carl H. Sondergeld,et al.  New Pore-scale Considerations for Shale Gas in Place Calculations , 2010 .

[9]  George Koperna,et al.  Reservoir Modeling in Support of Shale Gas Exploration , 2009 .

[10]  A. Seidel-Morgenstern,et al.  Computational investigation of longitudinal diffusion, eddy dispersion, and trans-particle mass transfer in bulk, random packings of core-shell particles with varied shell thickness and shell diffusion coefficient. , 2015, Journal of chromatography. A.

[11]  I. Johnstone,et al.  Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .

[12]  M. Tabaka,et al.  Taylor dispersion analysis in coiled capillaries at high flow rates. , 2013, Analytical chemistry.

[13]  George Waters,et al.  Evaluating Barnett Shale Production Performance-Using an Integrated Approach , 2005 .

[14]  J. J. Arps.  Analysis of Decline Curves , 1945 .

[15]  Dongxiao Zhang,et al.  Ensemble Based Characterization and History Matching of Naturally Fractured Tight/Shale Gas Reservoirs , 2010 .

[16]  Dongxiao Zhang,et al.  Quantitative dynamic analysis of gas desorption contribution to production in shale gas reservoirs , 2015 .

[17]  Peter P. Valko,et al.  A Better Way To Forecast Production From Unconventional Gas Wells , 2010 .

[18]  T. W. Doe,et al.  A Discrete Fracture Network Approach For Evaluation of Hydraulic Fracture Stimulation of Naturally Fractured Reservoirs , 2010 .

[19]  C. Cipolla,et al.  Reservoir Modeling in Shale-Gas Reservoirs , 2010 .

[20]  Juliana Y. Leung,et al.  History matching and uncertainty quantification of discrete fracture network models in fractured reservoirs , 2017 .

[21]  Dilhan Ilk,et al.  Exponential vs. Hyperbolic Decline in Tight Gas Sands: Understanding the Origin and Implications for Reserve Estimates Using Arps' Decline Curves , 2008 .

[22]  A. Ardeshir Goshtasby,et al.  Curve Fitting by a Sum of Gaussians , 1994, CVGIP Graph. Model. Image Process..

[23]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[24]  Dennis Denney,et al.  Practical Solutions for Pressure-Transient Responses of Fractured Horizontal Wells in Unconventional Reservoirs , 2010 .

[25]  John Killough,et al.  Beyond Dual-Porosity Modeling for the Simulation of Complex Flow Mechanisms in Shale Reservoirs , 2013, ANSS 2013.

[26]  G. Taylor.  Dispersion of soluble matter in solvent flowing slowly through a tube , 1953, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[27]  Michael R. Inggs,et al.  Gauss-Newton filtering incorporating Levenberg-Marquardt methods for tracking , 2013, Digit. Signal Process..

[28]  G. Taylor.  Conditions under which dispersion of a solute in a stream of solvent can be used to measure molecular diffusion , 1954, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[29]  John R. Fanchi,et al.  Probabilistic Decline Curve Analysis of Barnett, Fayetteville, Haynesville, and Woodford Gas Shales , 2013 .

[30]  Dilhan Ilk,et al.  Integrating Multiple Production Analysis Techniques To Assess Tight Gas Sand Reserves: Defining a New Paradigm for Industry Best Practices , 2008 .

[31]  Irina V. Stepanova,et al.  On thermal diffusion separation in binary mixtures with variable transport coefficients , 2015 .

[32]  Rajagopal Raghavan,et al.  Comparison of Fractured Horizontal-Well Performance in Conventional and Unconventional Reservoirs , 2009 .

[33]  F. Javadpour.  Nanopores and Apparent Permeability of Gas Flow in Mudrocks (Shales and Siltstone) , 2009 .

[34]  Shahab D. Mohaghegh,et al.  Coupling numerical simulation and machine learning to model shale gas production at different time resolutions , 2015 .

[35]  Dennis Denney.  Fracture- and Production- Data Integration With Discrete- Fracture-Network Models , 2000 .

[36]  John Killough,et al.  Beyond dual-porosity modeling for the simulation of complex flow mechanisms in shale reservoirs , 2013, Computational Geosciences.

[37]  Christopher R. Clarkson,et al.  History-matching and forecasting tight/shale gas condensate wells using combined analytical, semi-analytical, and empirical methods , 2014 .

[38]  Quinn R. Passey,et al.  From Oil-Prone Source Rock to Gas-Producing Shale Reservoir - Geologic and Petrophysical Characterization of Unconventional Shale Gas Reservoirs , 2010 .

[39]  S. Paramasivam,et al.  Experimental investigations on Ant Colony Optimized PI control algorithm for Shunt Active Power Filter to improve Power Quality , 2015 .

[40]  Luke D. Connell,et al.  A sequential model of shale gas transport under the influence of fully coupled multiple processes , 2015 .

[41]  Z. Liao,et al.  Multiple charges to Sinian reservoirs in the middle Sichuan basin, SW China: Insight from the adsorbed/occluded hydrocarbons in solid bitumens , 2015 .

[42]  J. Quinn.  Evaluation of Taylor dispersion injections: determining kinetic/affinity interaction constants and diffusion coefficients in label-free biosensing. , 2012, Analytical biochemistry.

[43]  Yuhui Shi,et al.  Particle swarm optimization: developments, applications and resources , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[44]  Heng Kuang,et al.  Fixture layout optimization in multi-station assembly processes using augmented ant colony algorithm , 2015 .

[45]  D L Massart,et al.  Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals part I: peak detection. , 2005, Journal of chromatography. A.

[46]  Spas D. Kolev,et al.  Mathematical modelling of flow-injection systems , 1995 .

[47]  Erno Pungor,et al.  Mathematical modelling of single-line flow-injection analysis systems with single-layer enzyme electrode detection Part 1. Development of the mathematical model , 1990 .

[48]  Chen Ling,et al.  A new Levenberg-Marquardt type algorithm for solving nonsmooth constrained equations , 2014, Appl. Math. Comput..

[49]  R. Marc Bustin,et al.  Impact of mass balance calculations on adsorption capacities in microporous shale gas reservoirs , 2007 .

[50]  Louis Mattar,et al.  Practical Analytical Model To Simulate Production of Horizontal Wells With Branch Fractures , 2012 .

[51]  Kamy Sepehrnoori,et al.  Simulation of gas desorption and geomechanics effects for unconventional gas reservoirs , 2014 .

[52]  Yaqing Ding,et al.  A method of approximate fractional order differentiation with noise immunity , 2015 .

[53]  O. Rioul,et al.  Wavelets and signal processing , 1991, IEEE Signal Processing Magazine.

[54]  John R. C. Robinson,et al.  Understanding Gas Production Mechanism and Effectiveness of Well Stimulation in the Haynesville Shale Through Reservoir Simulation , 2010 .

[55]  Shahab D. Mohaghegh,et al.  Full field reservoir modeling of shale assets using advanced data-driven analytics , 2016 .

[56]  Asif Iqbal,et al.  Levenberg-Marquardt method for solving systems of absolute value equations , 2015, J. Comput. Appl. Math..

[57]  Rajagopal Raghavan,et al.  Effect of Discontinuous Microfractures on Ultratight Matrix Permeability of a Dual-Porosity Medium , 2012 .

[58]  Luke D. Connell,et al.  Reservoir simulation of free and adsorbed gas production from shale , 2015 .

[59]  Peter P. Valko,et al.  Assigning value to stimulation in the Barnett Shale: a simultaneous analysis of 7000 plus production hystories and well completion records , 2009 .

[60]  Anh N. Duong,et al.  Rate-Decline Analysis for Fracture-Dominated Shale Reservoirs , 2011 .

[61]  F. Javadpour,et al.  Nanoscale Gas Flow in Shale Gas Sediments , 2007 .