Sara Godoy del Olmo Calculation of contaminated soil volumes : Geostatistics applied to a hydrocarbons spill Lac Megantic Case
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1 wwwnvisol-canadaca Sara Godoy dl Olmo Calculation of contaminatd soil volums : Gostatistics applid to a hydrocarbons spill Lac Mgantic Cas
2 Gostatistics: study of a PH contamination CONTEXT OF THE STUDY This study was conductd for pdagogical purposs In Jun 24 a gostatistical training was prformd for th Environmntal Ministry of Qubc and for othr public and privat companis in ordr to bttr undrstand th Gostatistical mthod and its applications to th contaminatd sits Th data st obtaind in th Lac Mgantic first charactrizations was usd for prforming th study cas during this training 2
3 Gostatistics: study of a PH contamination Ptrolum Hydrocarbons 3
4 Gostatistics: study of a PH contamination OBJECTIVES OF THE GEOSTATISTICAL STUDY Th gostatistical tratmnt has bn prformd in ordr to: Accuratly undrstand th contaminants bhaviour in soil (corrlations btwn contamination and dpth/topography/gology ) Onc th bhaviour of th contamination is stablishd, w prform a contamination mapping in ordr to visualiz th pollution migration Dlinat, if possibl, th pollution xtnt and th volums of contaminatd soil affctd by th PH spill 4
5 Gostatistics: study of a PH contamination Rmmbr: A gostatistical study is conductd as follows: Data fild intgration 2 Exploratory Data Analysis 3 Variogram fitting 4 Intrpolation mthods: Krigging / Simulations 5 3D mapping / Estimat of contaminatd soil volums 5
6 Gostatistics: study of a PH contamination Intgrating th fild data Laboratory data - In total, 45 PH laboratory analyss - Prfrntial sampling prformd in surfac fills - Maximum sampling dpth = 8 m Fild Data: gology - Fills layr (-2m) and natural soil (silt and clay) until 8 m dpth Rmdiation thrshold ppm for th PH Fild data must b go-rfrncd in a coordinat X Y Z systm 6
7 Gostatistics: study of a PH contamination 2 Exploratory Data Analysis Objctivs: Gological study, Contamination bas map, Quick statistics, histograms Corrlations btwn concntration and dpth/gology, Exprimntal variogram construction
8 Gostatistics: study of a PH contamination 2 Exploratory Data Analysis Contamination bas map 9 Nb Sampls: Minimum: Maximum: Man: Std Dv: 8 s i c n u q r F Contamin C-C5
9 Gostatistics: study of a PH contamination 2 Exploratory Data Analysis Corrlation btwn concntration and dpth Th highst concntrations ar masurd btwn 5 and m dpth Concntration moynn n C-C5 (ppm) 6 529, ,5 53,9 2 9,5 6, ,33 3,25,38 33,33
10 Gostatistics: study of a PH contamination 2 Exploratory Data Analysis Sampling fills Sand, gravl, Silt-F Natural soil Silt-NS, clay, organic mattr
11 Gostatistics: study of a PH contamination 2 Exploratory Data Analysis Corrlation btwn concntration and gology Man Minimum Lithology Cod Frquncy Effctiv 2 Gravl 2, ,53 428,9 3 Sand 3 5, ,8 99,9 4 Silt_F 4, ,4 35,4 5 Silt_NS 5 28, 26 8,95 254, Clay, 3 6 Org Mattr 6,6 3,4 28, (PH ppm) concntration Maximum concntration
12 Gostatistics: study of a PH contamination 2 Exploratory Data Analysis Exprimntal Variogram Construction B/ Isotrop Dirctional Variogram NO/D9 5 C C n i m a t n o C : m a r g o i r a V N D Contamin C-C5 2 3 Distanc (m) 5 C C n i m a t n o C : m a r g o i r a V D-9 Contamin C-C5 2 3 Distanc (m) 4 5
13 Géostatistiqu: étud d un contamination aux HP t au Ni 3 Variogram Fitting B/ Isotrop Dirctional Variogram NO/D9 5 C C n i m a t n o C : m a r g o i r a V Distanc (m) N D C C n i m a t n o C : m a r g o i r a V Distanc (m) 3
14 Gostatistics: study of a PH contamination 3 Variogram Fitting Cross Validation Error 3D Variogram 4 Standard rror Man Varianc Prcntag of robust data Corrlation Cofficint Z/Z*
15 Gostatistics: study of a PH contamination 4 Intrpolation mthod: ordinary krigging Ptrolum Hydrocarbons -2 m 5
16 Gostatistics: study of a PH contamination 4 Intrpolation mthod: ordinary krigging Ptrolum Hydrocarbons 2-25 m 6
17 Gostatistics: study of a PH contamination 4 4 Intrpolation mthod: ordinary krigging Ptrolum Hydrocarbons 25-5 m
18 Gostatistics: study of a PH contamination 4 Intrpolation mthod: ordinary krigging Ptrolum Hydrocarbons 5-8 m 8
19 Gostatistics: study of a PH contamination 4 Intrpolation mthod: ordinary krigging Ptrolum Hydrocarbons 3D viw 9
20 Gostatistics: study of a PH contamination 4 Intrpolation mthod: ordinary krigging Ptrolum Hydrocarbons Concntrations > ppm - 3D viw Is th whol sit contaminatd? Why? 2
21 Gostatistics: study of a PH contamination 4 Intrpolation mthod: ordinary krigging Krigging rproducs th xpctd valu of th distribution: stimats ar strongly influncd by th man valu of th distribution Original data histogramm - PH Nb Sampls: Minimum: Maximum: Man: Std Dv: 5 s i c n u q r F Nb Sampls: Minimum: Maximum: Man: Std Dv: 5 s i c n u q r F Krigging histogramm- PH Contamin C-C Contam HP stimatd Sara 3D omni
22 Gostatistics: study of a PH contamination 5 Intrpolation Mthods: Conditional simulations Krigging Conditional Simulations Krigging allows rproducing th xpctd Each simulation rspcts th valus valu of th distribution: stimats ar obsrvd in th sampl points Man and strongly influncd by th man valu varianc ar prsrvd in ach ralization Svral random fonctions whit th sam man and varianc can hav th sam variogram Allows only on contamination Quantifying possibl 22 th Simulations can rproduc th statistics of ordr (histogram) and 2 (variogram) mapping of th Prforming a larg numbr of simulations allows to bttr rproduc th ral divrsity of possibl cass, spcially if w ar considring a random variabl uncrtainty is not Th uncrtainty is quantifid so it is possibl to asss th risk of th projct
23 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Conditional simulations allow us to prform svral charts (with qual probability) to bttr rflct th divrsity of ral possibl cass Simulation : grid 5*5*5 m 23
24 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Simulation 3 : grid 5*5*5 m 24
25 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Simulation 25: grid 5*5*5 m tc 25
26 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Prforming a post-tratmnt of conditional simulations allows to ask th following qustions: Whr ar th contaminatd aras? This qustion is usd to locally stimat th risk of xcding th rmdiation thrshold What is th volum of contaminatd soil? This qustion is usd to stimat th ovrall lvl of contamination in th study ara How to answr ths qustions??? 26
27 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Whr ar th contaminatd aras? This qustion is usd to locally stimat th risk of xcding th rmdiation thrshold Stting a rmdiation thrshold probability map for th occurrnc of PH in soil (for ach bloc) in concntrations highr than 5 ppm 2
28 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Blocks showing a probability of xcding th rmdiation thrshold gratr than 6% 28
29 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Which risk lvl ar w willing to accpt? How to manag blocks showing an uncrtain stimat? Blocks having a probability of xcding th rmdiation thrshold (5 ppm) btwn 3 and 6% 29
30 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations What is th volum of contaminatd soil? This qustion is usd to stimat th ovrall lvl of contamination in th study ara 9 8 P95 ( ) P9 ( 44235) P85 ( ) Optimistic volum s i c n u q r F 6 5 P5 ( ) Most probabl volum P5 ( 539 P ( 554 P 5 ( Volum (m3) Risk curv 3 Pssimistic Volum
31 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Prforming conditional simulations shows that: Th stimatd volum of contaminatd soil is btwn 54 m3 (pssimistic volum) and m3 (optimistic volum) Th most probabl volum is m3, which corrsponds to 25% probability of xcding th rmdiation thrshold (low risk) Th uncrtain volum (probability btwn 3% and 6%) rprsnts a total volum of 23 8 m3 This volum rprsnts 48% of th most probabl contaminatd volum announcd by th risk curv 3
32 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Th calculations show a grat uncrtainty of th contaminatd soil stimat 2 ) m ( Z Sampling barly prformd from 5 m dpth X (m) 3 4 5
33 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations If th stimat is stoppd at 5 m dpth: 9 8 P95 ( 2855) P9 ( 24) P85 ( 29) s i c n u q r F Th diffrnc btwn th pssimistic and optimistic volums is lss important, Th most probabl volum is 248,25 m3, which is half of th uncrtain volum calculatd abov, and corrsponds to approximatly 25% probability of xcding th rmdiation thrshold Th volum of contaminatd soil showing uncrtain stimation (3% to 6% probability of xcding th thrshold) is m3 This volum rprsnts 25% of th most probabl contaminatd volum (P5) announcd by th risk curv 6 5 P5 ( 24825) P5 ( 285) P ( P 5 ( Volum (m3) 3 35
34 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Mapping : Soil having 25% probability or mor of bing abov th rmdiation thrshold and corrsponding to th most probabl contaminatd volum 34
35 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Changing th grid: blocks siz = 25*25* m Blocks having a probability gratr than 6% of xcding 5 ppm 35
36 Gostatistics: study of a PH contamination 5 Intrpolation Mthod: Conditional Simulations Changing th grid: blocks siz = 25*25* m It is possibl to produc maps suitabl for dcontamination which will b basd on th risk w ar willing to tak in ordr to dfin a ral stratgy for th rmdiation projct Blocks with 3 to 4% probability of xcding th critrion Blocks with 4 to 6% probability of xcding th critrion Blocks with mor than 6% probability of xcding th critrion 36
37 Gostatistics: study of a PH contamination Comparison btwn diffrnt mthods: Polygons vs Gostatistics Polygons mthod prformd according to th obsrvd gology (thicknss of th fills layr) Total volum 3 m3 to 26 3 m3 3
38 Gostatistics: study of a PH contamination Comparison btwn diffrnt mthods: Polygons vs Gostatistics Risk curv Risk curv prformd on th fills for th north ara, along th railways P95 ( 6525) P9 ( 685) P85 ( 25) 9 8 s i c n u q r F 6 5 P5 ( 95) P5 ( 8595) P ( 8865) P 5 ( Volum (m3)
39 Gostatistics: study of a PH contamination Conclusions Prforming th gostatistical study highligths th following information : Gostatistics provid a cohrnt analysis of data collctd at ach stp of a contaminatd sit charactrization by prforming statistical procssing of spatial data Gostatistics ultimat goal is to dtrmin th uncrtaintis associatd to intrpolation mthods in ordr to rduc th financial risks of rmdiation sits projcts Th choic of th gostatistical mthod usd for ach projct has a larg influnc whn making stimats, spcially if th original data dos not show a clar spatial structur To mak rlvant calculations, it is ncssary to conduct a comprhnsiv analysis of th input data bfor intgrating it into th gostatistical tratmnt Each choic must b justifid by th gostatistical thoris but also judgd by th xprts working on contaminatd sits 39
40 4 Thank you for your attntion
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