1
Removal of Total Petroleum Hydrocarbons (TPHs) and Polycyclic 1
Aromatic Hydrocarbons (PAHs) in Spent Synthetic-Based Drilling 2
Mud 3
Using Organic Fertilizer 4
5
6
Abstract 7
Treatment and disposal of spent(used)drilling mud have become animportant environmental 8
challenge in the oil and gas industry. Total Petroleum Hydrocarbons (TPHs) and Polycyclic 9
Aromatic Hydrocarbons (PAHs) constitute the major contaminants in spent drilling mud. In this 10
study, five spentsynthetic-based drilling mud samples were collected from five oil fields in the 11
Niger Delta. Samples collected on day 0 were analyzed for TPHs and PAHs. Concentrations 12
higher than thepermissible regulatorylimits were recorded. The efficacy of urea fertilizer in the 13
remediation of TPH-and PAH-impacted mud was investigated. Six sub-samples and six control 14
sub-samples were tested bi-weekly for 12 weeks with 20g, 25g, and 30g doses of urea fertilizer per 15
20L of spent mud for each of the five samplesrepresenting each individual oil field (marked A 16
through E). Removal of TPHs and PAHs with urea fertilizer treatment proved to be fast and 17
efficient. In 6 weeks, with a dose of 1.5g/L, over 98% removal of TPHswas recorded, and more 18
than 94% of PAHs, and in 12 weeks, more than 99.5% removal was recorded for both. The 19
residual levels of TPHs and PAHs met Department of Petroleum Resources(DPR: Nigeria) and US 20
EPA limits for land disposal. Mathematical models with agoodness of fit(R2) of 0.999, were 21
developed to predict the rate of thedegradation processes. 22
Keywords: Spent Drilling Mud, Niger Delta, Total Petroleum Hydrocarbons, and Polycyclic 23
Aromatic Hydrocarbons, Biodegradation, Urea Fertilizer, Mathematical Model. 24
25
1. INTRODUCTION 26
Drilling is one of the major chemical intensive operations in oilfields that generates wastes, which 27
can impact the environment. (Coussotet al., 2004; Ebrahimi et al., 2012; Zhang et al.,2011; Ball et 28
al., 2012; Hu et al., 2014). In drilling operations, two main types of wastes are generated, drill 29
cuttings and spent drilling mud(Mkpaoroetal.,2015;Bakke et al.,2013;Bamberger and 30
Oswald,2012;Bansal and Sugiarto,1999).Drilling fluids, including synthetic base fluids (SBFs), play 31
important roles in drilling operations by providing relatively better shale inhibition, lubricity, and 32
thermal stablity characteristics(Fomasieretal.,2017;Nahmad and Lepe, 2014;Ball et al., 2012). Other 33
SBF functions include lifting of drill cuttings from the well and controlling hydraulic pressure(Anon, 34
2011;Dankwaetal., 2018). 35
2
Total Petroleum Hydrocarbons(TPHs) and Polycyclic AromaticHydrocarbons(PAHs) are some of 36
the major contaminants of the spent drilling mud and they impact adversely on the environment if 37
carelessly disposedof(Fijałet al.,2015; Fontenot et al.,2013). Studies have shown that plant growth 38
is affected when petroleum hydrocarbon-impacted spent drillingmud is released on 39
land(Osisanya,2011). Levels of spent drilling mudabove a few percentages in soil (by weight) have 40
beenshown to degrade plant growth(Clements et al., 2010;Czekajet al.,2005). Improper disposal of 41
spent drilling mud into water bodiesendanger marine life (Anozie and Onwurah,2001).Safe 42
disposal of spentdrillng mud after drilling is a major problem in the oil and gas industry(Gross et 43
al.,2013; Hou et al.,2012;Onwukwe and Nwakaudu,2012). Most of the existing methods of 44
treatment like fixation,andthermal methods,have disadvantages ranging from high risk to personnel 45
to huge costs because of thehigh energy demands due to high temperature requirements(Liu et al., 46
2016;Kerri et al., 2013).Some of these existing methods of treatment require expensive and 47
sophisticated equipment with high capital and operating costs (Hu et al., 2014;Kerri et al.,2013; 48
Xieet al.,2015). 49
Bioremediation is the biological breakdown or biodegradation of contaminants(Bewley et al., 50
2001). It involves the microbial breakdown of organic compounds into less complex compounds, 51
mostly water, and carbon dioxide and sometimes methane(Patel et al., 2012). The rate and extent 52
of biodegradation depends on the population and type of microorganisms, the environment, and the 53
chemical structure of the contaminant(Semple et al., 2003). Most organic compounds are 54
biodegraded under aerobic conditions(Kauppi et al., 2011). Biodegradation of some organic 55
compounds has also occurred under anaerobic conditions, although at rates not as rapid as under 56
aerobic conditions(Akindeet al., 2012). Intrinsic bioremediation or natural attenuation is the 57
biodegradation of a target contaminant without intervention under an appropriate environmental 58
condition, available nutrients (mostly phosphate, nitrogen and sulfur), and 59
microorganisms(Ibieneet al., 2011). However, from regulatory point of view, the rate of intrinsic 60
bioremediation is slow because of time limits(Chikere et al., 2012b). As a result, enhanced 61
(engineered) bioremediation is required most of the time(Abdusalamet al.,2011;Kadaliet al., 62
2012). In engineered bioremediation, the rate of bioremediation is increased in two ways: 63
biostimulation and bioaugmentation(Abdusalamet al,2011;Bourceretet al., 2015). Biostimulation 64
3
was deployed in this study by use of urea fertilizer,as a source of nutrient to the indigenous 65
microorganisms, to biodegrade TPHs and PAHs in impacted, spent synthetic based mud. 66
Urea is one concentrated source of available nitrogen. It is widely used in agriculture as a fertilizer 67
and animal feed additive. Urea fertilizer is the most important nitrogenous fertilizer.It is called the 68
King of Fertilizers because of its high nitrogen content (about 46 percent). 69
It is a white crystalline organic chemical compound. It is neutral and can adapt to almost all the 70
land. It is a waste product formed naturally by metabolizing protein in humans as well as other 71
mammals, amphibians and some fish. The main function of urea fertilizer is to provide the plants 72
with nitrogen to promote green leafy growth. It can make the plants look lush, and it is necessary 73
for the photosynthesis of plants. Nitrogen is an important nutrient required for microbial growth. 74
Urea fertilizer is widely used in biostimulation because of its high nitrogen content. 75
Advantages of urea fertilizer include: highest nitrogen content (this percentage is much higher than 76
in other available nitrogenous fertilizers), low cost of production, no storage risk (not subject to 77
fire or explosion hazards), and wide application-urea fertilizer can be used for all types of crops 78
and soils and does not harm the soil. However, it is very soluble in water and hygroscopic, and 79
requires better packaging quality. 80
81 Mathematical models help to predict the expected outcome of experiments.This saves time and cost for 82
future jobs.More often the field and laboratory data are used to calibrate mulit- purpose regression models 83
of linear and/or higher order equivalence.The statistical approach was adopted in this study for model 84
development. 85
2. METHODOLOGY 86
2.1Area of Case Study 87
4
This study was carried out with spent, synthetic based mud (SBM) from five oilfields in the Niger 88
Delta. TheNiger Delta is located at an elevation of 96m above mean sea level. It lies between East 89 Longitude 5° and 8° and North Latitude 3° and 6°.Samples A, B, C, D and E were taken at 90 Longitude 5°9'40.58"East and Latitude5°19'17.71"North, Longitude 6°47'4.912"East and Latitude 91
3°11'37.644"North, Longitude 6°16'41.972"East and Latitude 4°11'42.948"North, Longitude 92 6°21'20.38"East and Latitude 4°54'28.648"North, Longitude 6°42'12.077"East and Latitude 93
4°59'30.057"North, respectively.( Figure 1.)The region has a population of 30 million people 94
(NBS,2006). Over 90% of Nigeria’s proven oil and gas reserves are located in the region ((Adati, 95 2012). The NigerDelta covers a coastline of 560km
2, and it is formed primarily by sediment 96
deposition(Osinowoet al,2018). It’s a rich mangrove swamp covering over 20,000km2 within 97
wetlands of 70,000km2 (Ekubo and Abowei,2011). Oil was first discovered in the delta by Royal 98
Dutch Shell (Shell Nigeria), formerly Shell-BP, in 1957 at Oloibiri, and production began in 1958. 99
The oil and gas industry play significant role in Nigeria’s economy, accounting for about 90% of 100
its gross income(Abubakar,2014). Figure 1 shows the map of Niger Delta and drilling mud sample 101 locations. 102
103
Figure 1. Location map of study area 104
105
5
2.2 Data collection 106
Adequate quantities of the spent drillingmud from five oil fields were sampled from well-agitated 107
mud tanks and transported to the laboratory as quickly as possible to ensure that the parameters of 108
the mud did not change before testing. Convenience sampling method was used because of low 109
drilling activities in Nigeria,at the time of this study.In the laboratory, the samples were again 110
thoroughly agitated with sample mixers to ensure proper mixing.The samples were marked MUD-111
A to E and tested for baseline values of the physicochemical parameters (Table 2). For each 112
sample, 25 (twenty-five) sub samples of 20L each were created: (i) One sub-sample for baseline 113
studies; (ii) Eighteen (18) sub-samples for bioremediation treatment for Total Petroleum 114
Hydrocarbons(TPHs) and PAHs with urea fertilizer (6 sub-samples each for 20g, 25g, and 30g 115
doses); (iii) Six (6) sub-samples for control. The control samplesare the original spent drillingmud 116
without treatment. Urea fertilizer was used as a source of nutrients for the hydrocarbon utilizing 117
bacteria (HUB) for the remediation of the mud impacted with Total Petroleum Hydrocarbonsand 118
PAHs. Both the treated and control samples were tested bi-weekly for 12 weeks. The tests 119
conducted and methods used are shown in Table 1. 120
Table 1: Analytical methods employed in the study 121
Parameter Analytical Method STANDARD
TPHs and PAHs GC/FID (Agilent 7890A GC systems) ASTM D 3921
THB and HUB Total Plate Count ASTM D5465-16
Total Nitrogen Kjeldahl ASTM D8001-16e1
Temperature Meter reading ASTM E2251-14
pH Meter reading ASTM D1293-18
Moisture Content Gravimetric method ASTM D2216-98
CO2 Standard method for dissolved carbon
dioxide in liquid ASTM D513-16
DO Standard method for dissolved oxygen in
liquid ASTM D888-12e1
Phosphorous Total phosphorous-EPA method EPA 365.1
6
TOC Standard test method for total carbon and
organic carbon in liquid by ultraviolet and
infrared dictation
ASTM D4839-03(2017)
122
2.3 Predictive model 123
Nonlinear regression analyses were applied in modeling the duration of the effective biological 124
treatment of the spent drilling mud. XLSTAT 2018 was the statistical tool employed as an aid for 125
the model development (Ziegler, 2005; Nwaogazie, 2011). 126
127
3. RESULTS AND DISCUSSION 128
3.1 Results 129
Baseline physicochemical parameters of spent drilling mud samples 130
The baseline values of the physicochemical parameters of the spent drilling mud are shown in 131
Table 2. Nigerian and US EPA effluent limits for TPHs and PAHs are also shown in Table 3.It can 132
be seen that spent drilling mud from different oil wells have varying concentrations of the 133
contaminants. 134
135
Table 2: Physico-chemical parameters of the spent drilling muds 136
S/NO
Parameters
A
Sample
B
C
D
E
1 pH 7.5 ± 0.01b 7.3 ± 0.01
a 7.8 ± 0.00
c 7.4 ± 0.09
a 7.9 ± 0.00
c
2 Temperature(oC) 28 ± 0.00
a 28.3 ± 0.10
b 28.7 ± 0.05
c 29.0 ± 0.00
d 28.5 ± 0.10
bc
3 Nitrogen (mg/L) 0.06 ± 0.004b 0.08 ± 0.005
d 0.06 ± 0.004
b 0.04 ± 0.002
a 0.05 ± 0.003
ab
4 Potassium (mg/L) 2.0 ± 0.3ab
2.7 ± 0.3d 1.7 ± 0.2
a 2.2 ± 0.1
ab 2.0 ± 0.2
ab
5 Sodium (mg/L) 2.4 ± 0.03b 1.7 ± 0.02
a 2.3 ± 0.03
b 1.7 ± 0.10
a 2.4 ± 0.10
b
6 Calcium (mg/L) 13.4 ± 0.2a 16.3 ± 0.2
c 17.4 ± 0.00
d 14.7 ± 0.10
b 19.10 ± 0.2
e
7 Phosphate(mg/L) 2.3 ± 0.03a 7.4 ± 0.03
d 7.6 ± 0.05
e 5.8 ± 0.03
c 3.8 ± 0.04
b
8 Conductivity 2.58 ± 0.02a 2.68 ± 0.02
b 2.84 ± 0.03
c 2.62 ± 0.02
ab 2.86 ± 0.02
c
9 Chlorides (mg/L) 18.8 ± 0.2a 22.2 ± 0.4
b 23.3 ± 0.43
c 19.64 ± 0.04
a 25.47 ± 0.03
d
10 TOC (%) 1.4 ± 0.2a 1.8 ± 0.2
a 1.95 ± 0.3
a 2.0 ± 0.3
a 1.6 ± 0.3
a
11 DO (mg/L) 7.1 ± 0.3a 7.95 ± 0.45
a 10.4 ± 0.4
b 8.4 ± 0.5
a 7.2 ± 0.4
a
12 Moisture Content (%) 8.9 ± 0.6bc
9.2 ± 0.4bc
7.6 ± 0.3ab
10.3 ± 0.3c 6.8 ± 0.5
a
13 CO2 (mg/L) 1.6 ± 0.1a 1.8 ± 0.1
a 2.2 ± 0.2
a 1.7 ± 0.3
a 2.1 ± 0.4
a
7
14 TPHs (mg/L) 6211 ± 10a 8591 ± 8
c 9474 ± 10
d 10110 ± 10
e 7482 ± 8
b
15 PAHs(mg/L) 82.0 ± 0.5a 94.6 ± 0.4
d 84.7 ± 0.3
b 86.25 ± 0.55
b 92.6 ± 0.4
c
16 THB (CFU/ml) 9.4 ± 0.1×105e
7.6 ± 0.02×105a
8.4 ±0.01×104b
9.3 ± 0.0×105d
8.9 ± 0.05×105c
17 HUB (CFU/ml) 4.3 ± 0.1×104c
6.3 ±0.1×104a
5.2 ± 0.01×105d
6.4 ±0.1×104e
9.9 ± 0.01×104b
a-e
Results are presented as mean ± standard error. Means with different superscript, the 137
homogenous subset of means, (a, ab, b, bc, c, d and e) within the same rows indicate significant 138
differences (p < 0.05), 139
140
Legend: 141
DO = Dissolved Oxygen; 142
TOC=Total Organic Carbon; 143
TPHs=Total Petroleum Hydrocarbons; 144
PAHs=Polycyclic Aromatic Hydrocarbons; 145
HUB=Hydrocarbon Utilizing Bacteria, and; 146
THB=Total Heterotrophic Bacteria. 147
148
Table 3: DPR (Nigeria) and US EPA guidelines and standards for TPHs and PAHs 149
Parameters Nigeria (DPR) USEPA
TPHs (Inland-fresh waters) (mg/L) 10 -
TPHs (Nearshore-brackish/saline waters) (mg/L) 20 -
TPHs (mg/L) - 5
PAHs (mg/L) 1 0.1
Sources:Department of Petroleum Resources (DPR2002);U.S. Environmental Protection Agency 150
(2018). 151
152
TPHs and PAHsbiodegradation 153
The laboratory test results for biodegradation of TPHs and microbial growth (HUB and THB) for 154
sample-A of the drilling mud impacted with Total Petroleum Hydrocarbonsand Polycyclic 155
AromaticHydrocarbonsusing 20g,25g, and 30g doses of urea fertilizer are presented in Figures 2 156
through 5. The population of the microorganisms varied from sample to sample. When stimulated 157
by the addition of nutrients, the microbial population count of the indigenous heterotrophic 158
bacteria increased. On amendment with 30g urea fertilizer, the total heterotrophic bacteria (THB) 159
grew from 9.40×105 CFU/ml and peaked in week 6 with a population of 6.27×10
8 CFU/ml before 160
8
dropping to 3.79×108 in week 12. The hydrocarbon utilizing bacteria (HUB) grew from 4.30×10
5 161
CFU/ml peaking in week 6 to 4.52×105 CFU/ml. After reaching this peak, the HUB started 162
dropping gradually to 2.63×108 in week 12. The same trend was observed with treatment using 163
20g, and 25g of urea fertilizer. This is represented in Figures 2 through 5. It is this growth that can 164
lead to the metabolizing of the hydrocarbons. 165
166
The biodegradation of hydrocarbon contaminants (TPHs and PAHs) for the study period of 12 167
weeks (using 20g, 25g, and 30g urea fertilizer amendments) is also shown in Figures 2 through 5. 168
The results show a sharp decrease in TPHs and PAHs concentrations in the first four weeks. This 169
indicates a period of active degradation by the microorganisms. After week 6, the degradation 170
level decreased, and that may be attributed to the microorganisms transiting into the stationary 171
phase after massive degradation had taken place between week 1 and 6. The results show an 172
average percentage degradation of 99.9% in 12 weeks for TPHs for the 5 samples studied. Also, 173
PAHs showed an average percentage degradation of 99.3% in 12 weeks for the five samples 174
175
176
4.30E+05
5.04E+07
1.00E+08
1.50E+08
2.00E+08
2.50E+08
3.00E+08
3.50E+08
4.00E+08
4.50E+08
5.00E+08
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 2 4 6 8 10 12 14
HU
B (
CF
U/m
l)
TP
H (
mg
/L)
Time (week))
20gTPH (mg/L)
25gTPH (mg/L)
30g TPH (mg/L)
20g HUB (CFU/ml)
25g HUB (CFU/ml)
30g HUB (CFU/ml)
9
Figure 2: Distribution of TPHs and HUB for Sample-A 177
178
179
180
Figure 3: Distribution of TPHs and THB for Sample-A 181
182
183
184
185
9.40E+05
1.01E+08
2.01E+08
3.01E+08
4.01E+08
5.01E+08
6.01E+08
7.01E+08
0
1000
2000
3000
4000
5000
6000
7000
0 2 4 6 8 10 12 14
THB
(CFU
/ml)
TPH
(mg/
L)
Time(week)
20g TPH (mg/L)
25g TPH (mg/L)
30g TPH (mg/L)
20g THB (CFU/ml)
25g THB (CFU/ml)
30g THB (CFU/ml)
10
186
187
188
11
189
Figure 4: Distribution of PAHs and HUB for Sample-A 190
191
4.30E+05
5.04E+07
1.00E+08
1.50E+08
2.00E+08
2.50E+08
3.00E+08
3.50E+08
4.00E+08
4.50E+08
5.00E+08
0
10
20
30
40
50
60
70
80
90
0 2 4 6 8 10 12 14
HU
B(C
FU/m
l)
PA
Hs(
mg/
L)
Time(week)
20g PAHS (mg/L)
25g PAHS (mg/L)
30g PAHS (mg/L)
20g HUB (CFU/ml)
25g HUB (CFU/ml)
30g HUB (CFU/ml)
12
192
Figure 5: Distribution of PAHs and THB for Sample-A 193
194
195
Control for Sample-A 196
The result of TPHs, PAHs, and the ratio of HUB and THB for Control Sample-A is shown in 197
Figure 6.The control sample did not show any appreciable decontamination. 198
199
200
9.40E+05
1.01E+08
2.01E+08
3.01E+08
4.01E+08
5.01E+08
6.01E+08
7.01E+08
0
10
20
30
40
50
60
70
80
90
0 2 4 6 8 10 12 14
TH
B (
CF
U/m
l)
PA
Hs
(mg
/l)
Time (week)
20g PAHS
(mg/L) 25g PAHS
(mg/L) 30g PAHS
(mg/L) 20g THB
(CFU/ml) 25g THB
(CFU/ml)
13
201
Figure 6: Distribution of TPHs, PAHs and HUB/THB ratio for Control Sample-A 202
203
Bioremediation Indicators for Sample-A 204
The result of bioremediation indicators for Sample-A using 30g of urea fertilizer is shown in 205
Figure 7. The corresponding result for thecontrol sample is presented in Figure 8.The 206
bioremediation indicators for the amended sample,reflected the decontamination process, as 207
against the control sample where the indicators were inactive. 208
209
0
10
20
30
40
50
60
70
80
90
1000
2000
3000
4000
5000
6000
0 2 4 6 8 10 12 14
PA
H(m
g/l
) ;
HU
B/T
HB
(%
)
TP
H (
mg
/l)
Time (weeks)
TPH (mg/L)
(HUB/THB)*100
PAHS (mg/L)
14
210
Figure 7: Distribution of bioremediation indicators for treatment of Sample-A using 30g urea fertilizer 211
212
213
0
2
4
6
8
10
12
14
16
18
0
5
10
15
20
25
30
35
0 2 4 6 8 10 12 14
P(m
g/L)
;N(m
g/L)
TOC
(mg/
L);C
O2
(mg/
L);O
2(m
g/L)
;pH
;Te
mp
(oC
);H
20
(%)
Tme(week)
TOC (%)
O2 (mg/L)
Temp(Oc)
P (mg/L)
N (mg/L)
CO2 (mg/L)
Ph
H2O
pH
CO2(mg/L)
H2O (%)
O2 (mg/L)
15
214
Figure 8: Distribution of bioremediation indicators for control Sample-A 215
216
Percentage removal of TPHs and PAHs in Sample-A in week six and week twelve 217
The percentage removal of TPHs and PAHs in Sample-A using 30g urea fertilizer, in week six and 218
twelve are shown in Figure 9. Also shown in Figure 9 is the corresponding TPHs and PAHs 219
reduction in the control samples for week six and twelve. 220
221
222
223
0
2
4
6
8
10
12
14
16
0
5
10
15
20
25
30
35
0 2 4 6 8 10 12 14
TOC
(%);
P(m
g/L)
;CO
2(m
g/L)
;O2(m
g/L)
;H2O
(%)
N(m
g/L)
;PH
;Tem
p(o
C)
Time(weeks)
N (mg/L)
Ph
Temp(oC)
TOC (%)
P (mg/L)
CO2 (mg/L)
O2 (mg/L)
H2O(%)
CO2 (mg/L)
H2O(%)
O2 (mg/L)
pH
16
Fig 9: Percentage removal of TPHs and PAHs in Sample-A for week 6 and 12 224
Model for the prediction of residual concentration of TPHs and PAHs, and microbial growth 225
using 20g, 25g, and 30g urea fertilizer treatment of spent synthetic based mud 226
The average of the collected data (MUD A-E) with respect to the experimental set up with 20g 227
urea fertilizer is presented in Table 4. 228
Table 4: Average results of Petroleum contaminants (TPHs and PAHs) degradation and microbial 229
counts using 20g of urea fertilizer 230
Time
(week)
THB
(CFU/ml)
HUB
(CFU/ml)
TPHs
(mg/L)
PAHs
(mg/L)
0 8.72×105 3.50×10
5 8373.6 88.06
2 6.24×106 2.94×10
6 3686.4 44.46
4 4.52×107 2.41×10
7 1620.4 21.88
6 3.33×108 2.12×10
8 714.6 11.48
8 2.86×108 1.80×10
8 314.0 5.72
10 2.45×108 1.52×10
8 139.0 2.86
12 2.10×108 1.29×10
8 62.0 1.48
231
Note: log10 equivalent of HUB and THB were used for the model 232
233
Table 5 shows a summary of regression power models of PAHs treatment using 20g urea fertilizer. 234
The exponential model is the best model with respect to R2, Mean Square Error, MSE and Root 235
Mean Square Error, RMSE values. 236
237
238
239
240
Table 5: Summary of regression power models of PAHs using 20 ,25 and 30g urea fertilizer treatment 241
Model Type Equation R2 MSE RMSE
17
± The best model with respect to R2, MSE and RMSE values 242
A repetition of regression power modeling was carried out for the other parameters, based on R2, 243
MSE, and RMSE values. The resultant model equations for biodegradation of TPHs and PAHs and 244
microbial growth using 20g, 25g, and 30g urea fertilizer are given in Table 6. 245
Table 6: Model equations for TPHs and PAHs degradation and microbial growth using 20g 25g 246
and 30g urea fertilizer treatment 247
Parameter Model Type Model Equations R2 MSE
20g urea fertilizer Application
TPHs (mg/L)
Exponential 8373.6e
-0.409t 1 1.191
PAHs (mg/L) Exponential 88.06e-0.341t
0.9999 0.054
HUB (CFU/ml) 4th order Polynomial 0.0009t4 – 0.0228t
3 + 0.1343t
2 + 0.2512t + 5.552 0.9944 0.021
THB (CFU/ml) 4th order Polynomial 0.0009t4 - 0213t
3 + 0.1253t
2 + 0.2333t + 5.9467 0.9943 0.017
25g urea fertilizer Application
TPHs (mg/L)
Exponential 8373.6e
-0.472t 1 8.662
PAHs (mg/L) 4th order Polynomial 0.0091t4 - 0.3283t
3 + 4.6054t
2 - 30.892t + 88.049 1 0.055
HUB (CFU/ml) 4th order Polynomial 0.0001t4 – 0.0242t
3 + 0.1413t
2 + 0.2734t + 5.5515 0.9944 0.022
THB (CFU/ml) 4th order Polynomial 0.0009t4 – 0.0224t
3 + 0.1315t
2 + 0.2475t + 5.947 0.9943 0.019
30g urea fertilizer Application
TPHs (mg/L)
Exponential 8373.6e
-0.571t 0.9997126.751
PAHs (mg/L) Exponential 88.06e-0.404t
0.9998 0.025
HUB (CFU/ml) 4th order Polynomial 0.001t4 – 0.0251t
3 + 0.1459t
2 – 0.2902t + 5.5507 0.9947 0.022
THB (CFU/ml) 4th order Polynomial 0.0001t4 – 0.0234t
3 + 0.1373t
2 + 0.2611t + 5.9473 0.9943 0.021
248
249
±Exponential PAHs = 88.06e-0.341t 0.9999 0.054 0.233
Polynomial
2nd order PAHs = 0.9493t2 - 17.805t + 82.596 0.9755 36.50 6.041
3rd order PAHs = -0.1001t3 + 2.7506t
2 - 25.81t + 87.4 0.9987 2.521 1.588
4th order PAHs = 0.008t4 - 0.2925t
3 + 4.1752t
2 - 29.053t + 88.059 1 0.06 0.244
5th order PAHs = -0.0001t5 + 0.0118t
4 - 0.3324t
3 + 4.3436t
2 - 29.288t + 88.071 1 0.108 0.328
6th order PAHs = -0.0002t6 + 0.0077t
5 -0.0937t
4 + 0.3291t
3 + 2.4632t2 -27.409t + 88.06 1
18
Parameter Model Type Model Equations R2 MSE
20g urea fertilizer Application
TPHs (mg/L)
Exponential 8373.6e
-0.409t 1.000 1.191
PAHs (mg/L) Exponential 88.06e-0.341t 0.9999 0.054
HUB
(CFU/ml)
4th order
Polynomial 0.0009t
4 – 0.0228t
3 + 0.1343t
2 + 0.2512t + 5.552
0.9944 0.021
THB
(CFU/ml)
4th order
Polynomial 0.0009t
4 - 0213t
3 + 0.1253t
2 + 0.2333t + 5.9467
0.9943 0.017
25g urea fertilizer Application
TPHs (mg/L)
Exponential 8373.6e
-0.472t 1 8.662
PAHs (mg/L) 4th order
Polynomial 0.0091t
4 - 0.3283t
3 + 4.6054t
2 - 30.892t + 88.049
1 0.055
HUB
(CFU/ml)
4th order
Polynomial 0.0001t
4 – 0.0242t
3 + 0.1413t
2 + 0.2734t + 5.5515
0.9944 0.022
THB
(CFU/ml)
4th order
Polynomial 0.0009t
4 – 0.0224t
3 + 0.1315t
2 + 0.2475t + 5.947
0.9943 0.019
30g urea fertilizer Application
TPHs (mg/L)
Exponential 8373.6e
-0.571t 0.9997 126.751
PAHs (mg/L) Exponential 88.06e-0.404t 0.9998 0.025
HUB
(CFU/ml)
4th order
Polynomial 0.001t
4 – 0.0251t
3 + 0.1459t
2 – 0.2902t + 5.5507
0.9947 0.022
THB
(CFU/ml)
4th order
Polynomial 0.0001t
4 – 0.0234t
3 + 0.1373t
2 + 0.2611t + 5.9473
0.9943 0.021
250
3.2 Discussion 251
19
Maximum allowable limits of hydrocarbon pollutants in waste media 252
The baseline results of the spent drilling mud (Table 2), show that the concentrations of TPHs and 253
PAHs in the five samples exceeded the maximum allowable limits for Nigeria and US EPA (Table 254
3). The high levels of TPHs and PAHsrecordedin the mud are capable of affecting the nutrient 255
levels, aeration and soil microbial diversity, and can even enter the food chain if disposed 256
untreated (Liu et al., 2016). This means that the spent mud has to be treated before disposal. The 257
Department of Petroleum Resources (DPR), the regulatory body in Nigeria, demands a reduction 258
of TPHs to less than 10mg/L and 20mg/L for inland and nearshore waters disposal respectively, 259
while the US EPA requires a concentration of less than 5mg/L. For PAHs, DPR requires a 260
concentration of less than 1mg/L, while the US EPA demands less than 0.1 mg/L for effluent 261
disposal. The remediation method employed in this study met the above limits for both TPHs and 262
PAHs. 263
The measured pH values were within the neutral range (provide the neutral pH range that was 264
measured here). Measured pH is an important factor that affects microbial growth (Wu, 2016). The 265
relationship between pH and microbial growth fits into a quadratic model: higher growth in neutral 266
media and lower in acidic and alkaline media. Temperature is in the mesophilic range. Both 267
temperature and pH conditions support bioremediation (Adam et al.,2015). ). Solubility of TPHs 268
and PAHs increases with temperature, which improves their bioavailability (Chen et al., 2015). 269
Most hydrocarbon degrading microorganisms perform optimally in the mesothermic temperature 270
range (20oC to 35
oC) (Wu, 2016). Though some microorganisms have been known to degrade 271
TPHs and PAHs under acidic and alkaline conditions (Shalluet al., 2014), most microorganisms 272
metabolize TPHs and PAHs in neutral pH ranges (Vila et al., 2015). 273
274
The measured dissolved oxygen had values that support bioremediation. Though bioremediation of 275
organic contaminants such as TPHs and PAHs can take place under both aerobic and anaerobic 276
conditions, it has been reported that the magnitude of anaerobic degradation is less than that of 277
20
aerobic (Xu et al., 2014). In aerobic degradation, dissolved oxygen is needed for respiration of the 278
microbes, and is required throughout the subsequent degradation process (Ren et al., 2015). The 279
aeration of the samples during biodegradation, provided more oxygen for the process. 280
The spent drilling mud contained low levels of micro nutrients such as nitrogen, phosphorous, 281
potassium and calcium. The measured organic matter contents (total organic carbon: TOC) of the 282
samples can be classified as average for spent drilling mud. TOC facilitates the moisture retaining 283
capacity of the mud (Chen et al., 2016). The measured average nitrogen level of 0.06% is low for 284
effective microbial growth (Xu et al.,2014). This is in line with several findings on hydrocarbon 285
contaminated sites (Azarbadet al., 2015). Also, the average phosphorous level of 5.4mg/L was low 286
and promoted microbial growth (Subathra, et al, 2013). The high carbon-to-phosphorous (C/P) 287
ratio resulting from crude oil addition, in crude oil-contaminated media, and the utilization of 288
inorganic phosphorous by the microorganisms, which attack the hydrocarbons, are responsible for 289
the low level of phosphorous recorded (Thenmozhiet al., 2012). 290
The ability of microorganisms to degrade hydrocarbons depends on the microbes’ population (Abu 291
et al., 2008). The spent drilling mud microorganisms’ number is usually in the range 104
to 107 292
Colony Forming Units (CFUs)/ml. This number should not be less than 103 per milligram of spent 293
drilling mud for successful biodegradation (Margesin, et al., 2003). The microbial load recorded in 294
the five samples were good enough for bioremediation (Sawulski, 2014). 295
Bioremediation is a rate limiting process,best described by the Monod equation 296
µ= (µmax *S)/ (KS +S) 297
where µmax =maximum specific growth rate, KS=Monod constant, S= substrate concentration. 298
21
The specific growth rate (µ)is controlled by the nature of the organism and the limiting nutrients 299
in the medium, such as N and P.This leads to the uptake of the contaminants and subsequent 300
removal i.e, the impacted medium is remediated. 301
Moisture is essential in the biodegradation process for the transportation of foods, nutrients and 302
waste products in and out of the microorganisms (Sawulskiet al.,2014). Moisture content of the 303
mud samples ranged from 6.8 to 10.3%. 304
The degradation of TPHs and PAHs support previous studies that by improving the limiting factors 305
to bioremediation of hydrocarbon contaminated spent drill mud, the degradation rate would be 306
improved (Ofoegbuet al., 2015). The pH remained largely neutral throughout the treatment. 307
The control samples showed low microbial growth. TPHs and PAHs degradation was also low. 308
Bioremediation indicators, TOC, nitrogen, dissolved oxygen, CO2, and phosphorous recorded 309
during the remediation period both for the stimulated samples and the control samples showed that 310
the degradation of TPHs and PAHs were a result of bioremediation. For the stimulated samples, 311
TOC, nitrogen, dissolved oxygen, and phosphorous, showed a decline because of their utilization 312
by the microorganisms, while CO2 and water, which are by-products of bioremediation, increased. 313
However, in the control samples, these parameters showed slight changes, which could be 314
attributed to other natural attenuation processes including volatilization, photo oxidation, etc. (Al-315
Awadhi, 2013;Abu and Dike,2008). 316
317
Nonlinear Regression Equations 318
Nonlinear regression equations developed for the petroleum contaminants (TPHs and PAHs) 319
treatment with 20g, 25g, and 30g urea fertilizer show a high goodness of fit, R2 of 0.999. With 320
these models, it may no longer be necessary to repeat all the experiments in the treatment of spent 321
22
drilling mud during bioremediation. Once the parameters in the model equations are established, 322
the model can be used to predict the residual concentration of TPHs and PAHs at any time, to a 323
very high accuracy. The microbial growth can also be predicted, accurately. This will give a good 324
idea of when treatment would be completed and save a lot of time and resources in the treatment of 325
spent drilling mud using this method. 326
327
4. CONCLUSION 328
Based on this study, the following conclusions can be drawn: 329
(1) Spent drilling mud from different fields have different concentrations of TPHs and PAHs. 330
(2) Urea fertilizer is effective in bioremediation of hydrocarbon impacted spent drilling mud. All 331
of the five amended samples achieved more than 97% removal in 6 weeks. A removal of up to 332
99.5% was achieved in 12 weeks. 333
(3) The residual levels of TPHs and PAHs in the five spent drilling mud samples tested complied 334
with Nigerian DPR and US EPA prescribed limits for disposal. 335
(4) Regression models of exponential and higher order polynomials were developed to predict with 336
high accuracy, the residual concentration of TPHs and PAHs, at any given time, in a hydrocarbon -337
impacted spent drilling mud using urea fertilizer. 338
339 340 341 342
343 344 345
346
23
347
348
349
. 350
Abdusalam, S.L., Bugaje, M., Adefila, S.S., and Ibrahim, S. (2011). Comparison of biostimulation 351
and bioaugumentation for remediation of soil contaminated with spent motor oil. Int. J. 352
Environ. Sci. Tech., 8,187-194. 353
Abu, G.O., Dike, P.O. (2008). A study of natural attenuation process involved in a microcosm 354
model of a crude oil-impacted wetland sediment in the Niger Delta. Biol. Technol., 4761 - 355
4767. 356
Abubakar, M.B. (2014). Petroleum potentials of the Benue Trough and Anambra basin:A regional 357
synthesis.Journal of Natural Resources,5,25-58 358
Adam, I., Miltner, A., and Kästner, M. (2015). Degradation of (13)C-labeled pyrene in soil-359
compost mixtures and fertilized soil. Appl Microbiol Biotechnol., 99,9813–9824. 360
Adati, A.K. (2012). Oil exploration and spillage in Niger Delta of Nigeria. Civil. Environ. Res., 361
2,2222 - 2863. 362
Akinde, S.B., Catherine, C.I., &and Omokaro, O. (2012). Alkane degradative potentials of bacteria 363
isolated from deep Atlantic oceans of the Gulf of Guinea. Bioremed. Biodegrad., 3,225 – 364
328 365
Al-Awadhi, H., Dashti, N., Khanafer, M., and Radwan, S. (2013) Bias problems in 366
cultureindependent analysis of environmental bacterial communities: a representative study 367
on hydrocarbonoclastic bacteria. SpringerPlus, 2,369. 368
Anon, A. (2011). Drilling Engineering Lecture Notes. Edinburgh, Scotland:Heriot-Watt 369
University, Department of Petroleum Engineering 370
Anozie, O., &and Onwurah, I. N. E. (2001) .Toxic effects of Bonny light crude oil in rats after 371
ingestion of contaminated diet. Nigerian J. Biochemistry and Molecular Biology, 16 372
(3),1035-1085. 373
Azarbad, H., Niklin´ska, M., Laskowski, R., van Straalen, N.M., van Gestel, C.A.M., Zhou, J., He, 374
Z.,Wen, C., &and Röling, W.F.M. (2015). Microbial community composition and 375
functions are resilient to metal pollution along two forest soil gradients. FEMS Microbiol. 376
Ecol., 91,1–11. 377
24
Bakke, T., Klungsøyr, J., and Sanni, S. (2013). Environmental impacts of produced water and 378
drilling waste discharges from the Norwegian offshore petroleum industry. Marine 379
environmental research, 92,154-169 380
Ball, A.S., Stewart, R.J., &and Schliephake, K. (2012). A review of the current options for the 381
treatment and safe disposal of drill cuttings. Waste, Manag Res.,30(5),457-473. 382
Bamberger, M., and Oswald, R. E. (2012). Impacts of gas drilling on human and animal health. 383
New Solut., 22,51–77. 384
Bansal, K.M., and Sugiarto, S. (1999).Exploration and Production Operations - Waste 385
Management A Comparative Overview: US and Indonesia Cases. Proceedings of Society 386
of Petroleum Engineers, SPE- 54345, Asia Pacific Oil and Gas Conference and Exhibition, 387
Jakarta, Indonesia. 388
Bewley, R.J.F., &and Webb, G. (2001). In situ bioremediation of groundwater contaminated with 389
phenols, BTEX and PAHs using nitrate as electron acceptor. Land Contam Reclam, 9,335–390
347. 391
Bourceret, A.,Cébron, A., Tisserant, E., Poupin, P., Bauda, P., Beguiristain, T., &and Leyval, C. 392
(2015). The bacterial and fungal diversity of an aged PAH- and heavy metal contaminated 393
soil is affected by plant cover and edaphic parameters. Microb. Ecol., 71,711–724. 394
Chen, L., Huang, M., and Jiang, X. (2015). Pilot tests of microbe-soil combined treatment of waste 395
drilling sludge. Natural Gas Industry (2), 100-105. 396
Chen, S., Peng, J., and Duan, G. (2016). Enrichment of functional microbes and genes during 397
pyrene degradation in two different soils. Journal of Soils and Sediments, 16, 417–426. 398
Chikere ,C.B., Surridge, K., Okpokwasili, G.C., Cloete, T.E. (2012b). Dynamics of indigenous 399
bacterial communities associated with crude oil degradation in soil microcsosms during 400
nutrient enhanced bioremediation. Waste Manag. Res., 30,225-36. 401
Clements, K., Veil, J.A., and Leuterman, A.J.J. (2010). Global Practices and Regulations for Land 402
application and Disposal of Drill Cuttings and Fluids. Proceedings of Society of Petroleum 403
Engineers, SPE-126565, International Conference on Health, Safety and Environment in oil 404
and Gas Exploration and Production, Rio de Janeiro, Brazil 405
Coussot, P., Bertrand, F., &and Herzhaft, B. (2004). Rheological behavior of drilling muds, 406
characterization using MRI visualization. Oil &and gas science and technology.59(1),23-407
29. 408
25
Czekaj, L., Fijał, J., Grzywnowicz, I., and Jamrozik, A. (2005). The influence of drilling waste on 409
selected soil properties. Wiertnictwo Nafta Gaz., 22/1,111-116. 410
Dankwa, O.K., Ackumey, S.S., and Amonn, F.I. (2018). Investigating the Potential Use of Waste 411
Vegetable Oils to Produce Synthetic Base Fluids for Drilling Mud Formulation. 412
Proceedings of the Society of Petroleum Engineers, SPE-185492-MS, Annual International 413
Conference and Exhibition, Lagos, Nigeria. 414
Department of Petroleum Resources (DPR). (2002). Environmental guidelines and standards for 415
the petroleum industry in Nigeria (EGASPIN) (Rev. Ed.),277-288.Lagos,Nigeria:Author 416
Ebrahimi, M., Sarikkhani, M.R., &and Fallah, R. (2012). Assessment of biodegradation efficiency 417
of some isolated bacteria from oil contaminated sites in solid and liquid media containing 418
oil.compounds. Int. Res. J. Appl. Basic Sci., 3(1),138-147. 419
Ekubo, A., &and Abowei, J. (2011). Aspects of Aquatic Pollution in Nigeria. Research Journal of 420
Environmental and Earth Sciences.3(6),673-693. 421
Fijał, J., Gonet, A., and Jamrozik, A. (2015). Characterization, properties and microstructure of 422
spent drilling mud from the point of view of environmental protection. AGH Drilling, Oil, 423
Gas,32(3),483--492. 424
Fomasier, F.C., Campo, M., Djuric, A., and Obando, D.M. (2017). Designing Environmentally 425
Conforming Drilling Fluids: Challenges and Considerations in Latin America. Proceedings 426
of the Society of Petroleum Engineers, Latin America and Caribbean Petroleum 427
Engineering Conference, Buenos Aires, Argentina. 428
Fontenot, B. E., Hunt, L. R., and Hildenbrand, Z. L. (2013). An evaluation of water quality in 429
private drinking water wells near natural gas extraction sites in the Barnett shale 430
formation.EnvironmentalScience&Technology,(47)17,10032– 10040. 431
Gross,S. A., Avens, H. J., Banducci, A. M., Sahmel, J., Panko, J. M., and Tvermoes, B. E. (2013) 432
.Analysis of BTEX groundwater concentrations from surface spills associated with 433
hydraulic fracturing operations. Journal of the Air & Waste Management 434
Association,(63)4,424–432. 435
Hou, B., Liang, C., Deng, H., Xie, S., Chen, M., and Wang, R. (2012). Oil removing technology of 436
residues from waste oil-based drilling fluid treated by solid-liquid separation. Journal of 437
Residuals Science & Technology.9(4) 438
Hu, J., Hu, Z., &and Zhang, H. (2014). A research and application of oily solid waste incineration 439
technology in Ansai oilfield. J. Sino-Global Energy,19(2), 84-88. 440
26
Ibiene, A.A., Orji, F.A., &and Orji-Nwosu, E.C.. (2011) Microbial population in crude oil-polluted 441
soils in the Niger Delta. Nig. J. Agri. Food Environ.,7(3), 8-13. 442
Kauppi, S., Sinkkonen, A., &and Romantschuk, M. (2011). Enhancing bioremediation of diesel-443
fuel-contaminated soil in a boreal climate: comparison of biostimulation and 444
bioaugmentation. Int Biodeterior Biodegrad., 65,359–368 445
Kerri, L. H., Nathan, T. H., Nathan, R. H. (2013). Forward osmosis treatment of drilling mud and 446
fracturing wastewater from oil and gas operations. J. Desalination, 312(1), 60-66. 447
Liu, X., Aughenbaugh, K., Nair, S., Shuck, M., &and van Oort, E. (2016). Solidification of 448
Synthetic-Based Drilling Mud using Geopolymers. Proceedings of Society of Petroleum 449
Engineers, SPE-180325, Deepwater Drilling and Completion Conference, 450
GavestonGalveston, Texas, USA. 451
Margesin, R., Labbe, D., Schninner, F.,Greer, C.W, &and Whyte, L.G. (2003). Characterisation of 452
Hydrocarbon Degrading Microbial Populations in Contaminated and Pristine Contaminated 453
Soils. Applied and Environmental Microbiology, 69(6),3985-3092 454
Mkpaoro,M.I.F., Okpokwasili, G.C., and Joel,O.F.(2015).A Review of Drill-Cuttings Treatment 455
and Disposal Methods in Ngeria-The Gaps and Way Forward. Proceedings of the Society of 456
Petroleum Engineers, SPE-140720t, Annual International Conference and Exhibition, Lagos, 457
Nigeria. 458
Nahmad, N., and Lepe, A. (2014). Treatment of Contaminated Synthetic Based Muds (SBM) Drilling 459
Waste in Block 47 Oman. Proceedings of the Society of Petroleum Engineers, SPE-54345, 460
Abu Dhabi international Petroleum Exhibition and Conference, Abu Dhabi, UAE. 461
Nigeria Bureau of Statistics (2006). National Population Census,Federal Republic of Nigeria 462
Nwaogazie, I.L. (2011) Probability and Statistics for Science and Engineering Practice (3rd ed.). 463
Enugu, Nigeria: De- Adroit Innovation. 464
Ofoegbu R.O., Momoh, Y.O.L., &and Nwaogazie I.L. (2015). Bioremediation of Crude Oil 465
Contaminated Soil Using Organic and Inorganic Fertilizers. J Pet Environ Biotechnol,, 6,1. 466
Onwukwe, S., and Nwakaudu, M.. (2012). Drilling wastes generation and management approach. 467
International Journal of Environmental Science and Development,3(3),252. 468
Osinowo,O.O.,Ayorinde, J.O.,Nwankwo, C.P.,Ekeng, O.M., and Taiwo, O.B (2018).Reservoir 469
description and characterisation of Eni field Niger Delta.J. Petrol Explor Prod 470
Technol,8,381-397 471
27
Osisanya, S. (2011). Waste Management Plan. Lecture Notes, African University of Science and 472
Technology, AUST, Abuja, Nigeria 473
Patel, V., Cheturvedula, S., &and Madamwar, D. (2012). Phenanthrene degradation by 474
Pseudoxanthomonas sp. DMVP2 isolated from hydrocarbon contaminated sediment of 475
Amlakhadi canal, Gujarat, India. J Hazard Mater.,201–202,43–51. 476
REFERENCE 477 Ren, G., Ren, W., Teng, Y., and Li, Z. (2015). Evident bacterial community changes but only 478
slight degradation when polluted with pyrene in a red soil. Frontiers in Microbiology,6, 22. 479
Sawulski, P., Clipson, N., and Doyle, E. (2014). Effects of polycyclic aromatic hydrocarbons on 480
microbial community structure and PAH ring hydroxylating dioxygenase gene abundance 481
in soil. Biodegradation, 25,835–847. 482
Semple, K.T.,Morriss, A.W.J., &and Patori, G.I. (2003). Bioavailability of hydrophobic organic 483
contents in soils: fundamental concepts and techniques for analysis. European Journal of 484
Soil Science,54(4), 809. 485
Shallu, S., Hardik, P., &and Jaroli, D.P. (2014). Factors affecting the rate of biodegradation of 486
polyaromaticpolycyclic aromatic hydrocarbons.International Journal of pure and applied 487
bioscience,2(3),185-202 488
Subathra, M.K., Immanuel, G., and Suresh, A.H. (2013). Isolation and identification of 489
hydrocarbon degrading from Ennore creek. Bioinformatics, 9(3),150-157. 490
Thenmozhi, R., Praveenkumar, D., Priy, E., Nagasathy, A., &and Thajuddin, N. (2012). Evaluation 491
of aromatic and polycyclic aromatic hydrocarbon degrading abilities of selected bacterial 492
isolates. J. Microbiol. Biotech. Res. 2(3), 445-449. 493
U.S. Environmental Protection Agency. (2018). Development Document for Final Effluent 494
Limitations Guidelines and Standards for Synthetic-Based Drilling Fluids and other Non-495
Aqueous Drilling Fluids in the Oil and Gas Extraction Point Source Category: EPA-821-B-496
00-013, U.S. Environmental Protection Agency. 497
Vila, J., Tauler, M., and Grifoll, M. (2015). Bacterial PAH degradation in marine and terrestrial 498
habitats. Curr Opin Biotechnol.,33,95–102. 499
Wu, Y. (2016). Effects of pH and polycyclic aromatic hydrocarbon pollution on thaumarchaeotal 500
community in agricultural soils. Journal of Soils and Sediments, 1–10. 501
28
Xie, S., Jiang, G., Chen, M., Li, Z., Mao, H., &and Zhang, M. (2015). Treatment Technology for 502
Waste Drilling Fluids in Environmental Sensitivity Areas. Energy Sources, Part A: 503
Recovery, Utilization, and Environmental Effects,37(8),817-824. 504
Xu ,Y., Sun, G., Jin, J., Liu, Y., Luo, M., Zhong, Z., and Liu, Z. (2014). Successful bioremediation 505
of an aged and heavily contaminated soil using a microbial/plant combination strategy. J 506
Hazard Mater., 264,430–438. 507
Zhang, A., Wu, S., and Liu, D. (2011). Characteristics and control of drilling waste in gas field. 508
Journal Industrial Safety and Environmental Protection,37(12), 29-31. 509
Ziegler, C.K. (2005). Using mathematical models to assess sediment stability.Integrated 510
Environmental Assessment and Management,2(1),44-50 511
Top Related