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008			161221s2015 enk ob 001 0 eng d
020			_a9780128030714 _qelectronic bk.
020			_a0128030712 _qelectronic bk.
020			_z9780128030707
020			_z0128030704
029	1		_aDEBSZ _b433547839
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029	1		_aAU@ _b000058365779
035			_a(OCoLC)907676403 _z(OCoLC)908073893
035			_a(OCoLC)ocn907676403
039		9	_y12-21-2016 _zhafiz _wmetacoll.MYUKM.updates.D20160920.T210208.sdallbooks.1 (perolehan)hafizupload21122016.mrc _x144
040			_aNST _beng _erda _epn _cNST _dNST _dOPELS _dCOO _dCDX _dUIU _dOCLCO _dE7B _dYDXCP _dIDEBK _dDEBSZ _dOCLCO _dEBLCP _dS9I _dOCLCF _dOCLCO
049			_aMAIN
050		4	_aTN870.57
072		7	_aTEC _x026000 _2bisacsh
082	0	4	_a622/.3382 _223
100	1		_aJamshidnezhad, Mohammad, _eauthor.
245	1	0	_aExperimental design in petroleum reservoir studies / _cMohammad Jamshidnezhad.
264		1	_aOxford, UK : _bElsevier : _bGulf Professional Publishing, _c2015.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
504			_aIncludes bibliographical references and index.
505	0		_aFront Cover; Experimental Design in Petroleum Reservoir Studies; Copyright Page; Contents; Biography; Preface; 1 Introduction; 1.1 Petroleum reservoirs; 1.2 Petroleum rock properties; 1.3 Volumetric calculations in a reservoir; 1.4 Reservoir heterogeneity; 1.5 Reservoir models; 1.6 Experimental design; 2 Reservoir modeling; 2.1 Introduction; 2.2 Sources of data for reservoir modeling; 2.3 Reservoir characterization; 2.3.1 Geophysical and geological data; 2.3.2 Engineering data; 2.3.2.1 Core data; 2.3.2.2 Well logging data; 2.3.2.3 Pressure transient data.
505	8		_a2.3.2.4 Properties of reservoir fluids2.3.2.5 Rock-Fluid data; 2.3.2.6 Initialization data; 2.3.2.7 Well and recurrent data; 2.4 Mathematical modeling; 2.4.1 Decline curve analysis; 2.4.2 Analytical models; 2.4.3 Numerical simulation; 2.5 Model verification; 3 Experimental design in reservoir engineering; 3.1 Introduction; 3.2 Errors in mathematical modeling; 3.3 Uncertainty in reservoir data; 3.3.1 Uncertainty in geophysical data; 3.3.2 Uncertainty in geological data; 3.3.3 Uncertainty in dynamic data; 3.3.4 Uncertainty in PVT data; 3.3.5 Uncertainty in field performance data.
505	8		_a3.4 Uncertainty analysis3.4.1 History matching; 3.4.2 Stochastic methods for uncertainty analysis; 3.4.2.1 Basic definitions; 3.4.3 Monte Carlo simulation; 3.5 Experimental design; 3.5.1 Basic rules in experimental design; 3.5.2 Outcomes of experimental design; 3.5.3 Designs; 3.5.3.1 Two-level full factorial designs; 3.5.3.2 Two-level fractional factorial designs; 3.5.3.3 Plackett-Burman design; 3.5.3.4 Three-level designs; 3.5.3.5 Latin hypercube design; 3.5.4 Response surface; 3.5.5 Sensitivity analysis; 3.5.5.1 Sensitivity analysis work flow; 4 Case studies; 4.1 Introduction.
505	8		_a4.2 Case study 14.2.1 Ninth SPE comparative solution problem; 4.2.2 Uncertain parameters; 4.2.3 Experimental design; 4.2.4 Response surfaces; 4.3 Case study 2; 4.3.1 Undersaturated fractured reservoir in the middle east; 4.3.2 Uncertainty parameters; 4.4 Case study 3; 4.4.1 PUNQ case; 4.4.2 Uncertain parameters; 4.5 Case study 4; 4.5.1 Steam assisted gravity drainage in a heavy oil reservoir; 4.5.2 Experimental design; 4.6 Case study 5; 4.6.1 Barnett shale gas reservoir; 4.6.2 Reservoir modeling; 4.6.3 Uncertainty parameters; 4.6.4 Experimental design; 4.7 Case study 6.
505	8		_a4.7.1 Miscible WAG injection4.7.2 Reservoir modeling; 4.7.3 Uncertain parameters; 4.7.4 Experimental design; Appendix: F distribution values; References; Index.
520			_aOne of the main duties for reservoir engineers is reservoir study, which starts when a reservoir is explored and it continues until the reservoir abandonment. Reservoir study is a continual process and due to various reasons such as complexity at the surface and limited data, there are many uncertainties in reservoir modelling and characterization causing difficulties in reasonable history-matching and prediction phases of study. This book concentrates on experimental design, a trusted method in reservoir management, to analyze and take the guesswork out of the uncertainties surrounding the underdeveloped reservoir. Case studies from the Barnett shale and fractured reservoirs in the Middle East are some of the examples included. Other discussions on uncertainty in PVT, field performance data, and relevant outcomes of experimental design will provide insight into how better data can improve measurement tools, your model, and your reservoir assets. -- _cEdited summary from book.
588	0		_aOnline resource; title from PDF title page (EBSCO, viewed April 22, 2015).
590			_aElsevier _bScienceDirect All Books
650		0	_aOil reservoir engineering _xMathematical models.
650		0	_aPetroleum _xGeology _xMathematical models.
650		0	_aPetroleum engineering _xMathematics.
650		7	_aTECHNOLOGY & ENGINEERING / Mining _2bisacsh
650		7	_aOil reservoir engineering _xMathematical models. _2fast _0(OCoLC)fst01044731
650		7	_aPetroleum engineering _xMathematics. _2fast _0(OCoLC)fst01059510
650		7	_aPetroleum _xGeology _xMathematical models. _2fast _0(OCoLC)fst01059288
655		4	_aElectronic books.
655		0	_aElectronic books.
776	0	8	_iPrint version: _w(OCoLC)907676403 _z9780128030714
856	4	0	_uhttps://eresourcesptsl.ukm.remotexs.co/user/login?url=http://www.sciencedirect.com/science/book/9780128030707
907			_a.b16400628 _b2022-11-03 _c2019-11-12
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998			_ae _b2016-08-12 _cm _dz _feng _genk _y0 _z.b16400628
999			_c613448 _d613448