Evaluation of produced water quality by using water quality indices in Heglig area, Sudan

According to the US Department of Energy (DOE), the term ‘produced water’ has been assigned to water trapped in underground formations and brought to the surface along with oil or gas (Clark & Veil 2009; Jahan & Strezov 2017). Oilfields are responsible for more than 60% of daily generated produced water worldwide (PWTAEO 2017). Despite its significance, petroleum is produced with large volumes of waste, with wastewater accounting for more than 80% of liquid waste (Azetsu-Scott et al. 2007; Ahmadun et al. 2009). In addition to the amount generated, another important factor to be considered regarding produced water is its complex composition, once it is a mixture of a variety of organic and inorganic compounds. Produced water generally has as its main constituents: oils and greases, dissolved solids, organic and inorganic salts, dissolved gases, bacteria, chemical additives, heavy metals, and sometimes even radionuclides can be found (Lyman et al. 2018; Zemlick et al. 2018). Thus, the potential effect associated with discharging this wastewater on the environment without appropriate treatment has become an important issue and its disposal requires meeting the environmental regulations. Therefore, it has become essential to assess the water quality to identify the pollutants, categorize the water use, and strategize the remedial measures to maintain ecological health. Water quality impairment is a substantial environmental hazard which affects a wide variety of stakeholders and interests, particularly those who participate in outdoor water-based recreational activities (Barnett et al. 2018). Over the last few decades, in order to assess the water quality, researchers from different parts of the world have developed a number of methodologies: heavy metal pollution index (HPI) (Mohan et al. 1996), heavy metal evaluation index (HEI) (Prasad et al. 2013), Canadian water quality index (CWQI) (CCME 2014), fuzzy comprehensive evaluation method, comprehensive pollution index method (C), and water quality index (WQI) (Boateng et al. 2016). This study focused on evaluating the produced water quality in the Heglig area in Sudan using weighted arithmetic water quality index method WAWQI, HEI, HPI, and CWQI by measuring minerals, radionuclides, and physiochemical parameters, and also considered the significance of evaporation in Heglig oilfield after the bioremediation.

Heglig area is located in the Muglad basin between south Kordofan state in Sudan and the Unity state in South Sudan, and is limited by latitudes 9° 45′ and 11° 15′ N and longitudes 28° 45′ and 30° 15′ E. Heglig area extends almost from a tropical zone to semi-arid savanna. The annual rainfall rises from 600 mm in the northern part of the area to more than 800 mm in the south (Whiteman 1971). Heglig area accommodates two oilfields, Heglig and Neem. In Heglig oilfield, the produced water of around 39,747 m³ per day is transferred from Heglig central processing facility ponds to bioremediation with a flow rate of 2,000 m³ per hour for treatment (mainly oil in water) and then transferred to the forestry area (Figures 1 and 2). In Neem oilfield, the produced water of around 11,129 m³ per day is stored in three ponds around the Neem processing facility.

Produced water samples were collected from the inlet and outlet line of the bioremediation at Heglig oilfield. In addition, other water samples were collected from the outlet produced water line at Neem oilfield. Samples were collected in clean screw-capped polypropylene bottles. For trace metal analysis, a well-mixed 100 mL acid preserved sample was placed into a pre-cleaned, labeled beaker, 5.0 mL concentrated HNO₃ was added, the beaker was placed in a heater in a hood and temperature was adjusted to 105 °C. More concentrated nitric acid was added until digestion was completed by observation of a clear solution. The beaker was removed from the heater, cooled, and diluted back to the original 100 mL volume with metal-free water in a volumetric flask. Then, samples were analyzed using inductively coupled plasma optical emission spectroscopy (ICP-OES) Vista-MPX manufactured by VARIAN Inc, USA. On-site measurement of pH and dissolved oxygen was performed using a pH meter HI 98128 manufactured by HANNA Instruments, Italy, and portable dissolved oxygen meter HQ30D manufactured by HACH LANGE GMBH, Germany. Total dissolved solids (TDS) and conductivity were measured using an EC/TDS/NaCl/C° meter HI 9835 manufactured by HANNA Instruments. Total hardness, chemical oxygen demand (COD) and alkalinity were determined by titration method according to APHA (2012). Radioactivity was analyzed using gamma spectrometer LB200 Becquerel monitor manufactured by BERTHOLD, Germany. Nitrate, ammonia, phenol, and total suspended solids (TSS) were analyzed by spectroscopic method using spectrophotometer DR 6000 manufactured by HACH LANGE GMBH. Oil in water was determined by IR oil content analyzer OCMA-310 manufactured by Horiba, Japan. Grade chemicals and analytical grade reagents were used in analysis.

Four quality evaluation methods were used in this study: WAWQI for physiochemical parameters, HPI, HEI, and CCME WQI for overall pollution parameter.

• The number of times by which an individual concentration is greater than (or less than, when the guideline is a minimum) the guideline is termed an ‘excursion’ and is expressed as follows in Equation (9): 

  

  (9)
• The collective amount by which individual tests are out of compliance calculated by summing the excursions of individual tests from their guidelines and dividing by the total number of tests. This parameter, referred to as the normalized sum of excursions, or NSE, is calculated in Equation (10): 

  

  (10)
• F₃ is then calculated by an asymptotic function that scales the normalized sum of the excursions from guidelines (NSE) to yield a range between 0 and 100. 

  

  (11)

The guideline values are obtained from the Sudanese ministry of energy and mining standards for produced water discharge limits (RPEPIS 2005). Once the CCME WQI value has been calculated, water quality is classified into one of the following categories:

• Excellent: (CCME WQI value 95–100) – water quality is protected with a virtual absence of threat or impairment; conditions are very close to natural or pristine levels.

• Good: (CCME WQI value 80–94) – water quality is protected with only a minor degree of threat or impairment; conditions rarely depart from natural or desirable levels.

• Fair: (CCME WQI value 65–79) – water quality is usually protected but occasionally threatened or impaired; conditions sometimes depart from natural or desirable levels.

• Marginal: (CCME WQI value 45–64) – water quality is frequently threatened or impaired; conditions often depart from natural or desirable levels.

• Poor: (CCME WQI value 0–44) – water quality is almost always threatened or impaired; conditions usually depart from natural or desirable levels (CCME 2014).

A total number of 11 physicochemical parameters; total hardness, alkalinity, pH, TDS, electrical conductivity, oil and grease, COD, phenol, DO, TSS, and nitrate were measured for Heglig and Neem produced water with their observed standard deviations and used to assess the quality of produced water with the Sudanese ministry of energy and mining standard limits for produced water discharge (RPEPIS 2005). Radioactivity was measured for Neem oilfield produced water and Heglig oilfield produced water before and after the bioremediation; the result was higher than RPEPIS guidelines in Neem produced water (21 Bq/L) and zero in Heglig oilfield produced water. Radioactivity was significantly high in Neem produced water due to the high tendency of scale formation. The scale is typically a mixture of carbonate and sulfate minerals. One of these sulfate minerals is barite which is the primary host of oilfield NORM and the radioactivity is from isotopes of radium and their decay products (Lauer et al. 2018). The descriptive statistics of water quality and heavy metal evaluation indices generated for Heglig and Neem produced water is shown in Tables 3–5. Total hardness, pH, and phenol values of Heglig oilfield produced water were significantly affected by evaporation, showing higher values in the Heglig oilfield outlet to bioremediation compared to the inlet sample but still lower than RPEPIS guidelines. The concentration of total hardness and pH value in Neem oilfield produced water was higher than RPEPIS guidelines. The alkalinity and nitrate value for Heglig oilfield inlet to bioremediation was slightly lower than the outlet sample and both samples (inlet and outlet to bioremediation) had alkalinity and nitrate levels lower than RPEPIS guidelines. Anaerobic degradation processes, such as denitrification and sulfate reduction, have a much greater impact on increasing alkalinity for the outlet sample of the bioremediation, as denitrification and sulfate reduction occur in the bioremediation, where there is an absence of oxygen. Both of these processes consume hydrogen ions, and this consumption of H⁺ increases the alkalinity (Thomas & Schiettecatte 2008). Nitrate appears in high concentrations in the water samples after the bioremediation due to dead aquatic organisms and plants and bird feces which are first decomposed to produce ammonia. Some bacteria in the water change this ammonia to produce nitrite, which is then converted by other bacteria to nitrate (Tang et al. 2011). Neem oilfield produced water alkalinity, TDS, electrical conductivity, and TSS has significantly standard deviations according to RPEPIS guidelines. TDS and electrical conductivity values of Heglig oilfield produced water were significantly affected by evaporation showing a higher value for the outlet to bioremediation compared to the inlet sample and exceeding RPEPIS guidelines for the outlet sample. The concentrations of COD, TSS, and conductivity in Heglig oilfield produced water before the bioremediation were higher than RPEPIS guidelines. COD is a measure of the capacity of water to consume oxygen during the decomposition of organic matter (APHA et al. 2012). High concentration of COD before the bioremediation is due to high concentration of oil in water. The oil in water was significantly affected by the bioremediation where it decreased to lower than the standard target from 11.3 to 1.5 for Heglig oilfield inlet and outlet to bioremediation, respectively. According to Elbrir et al. (2015), the efficiency of Heglig oilfield bioremediation in hydrocarbon treatment is about 88%. The concentrations of oil in water, COD, DO, and phenol in Neem oilfield produced water were within the standard values. Heglig oilfield had standard levels of DO according to RPEPIS guidelines. According to Franklin (2014), low dissolved oxygen is most commonly encountered in unshaded areas, which explains the lack of oxygen for the location of Neem oilfield and before the bioremediation, which is an unshaded area compared to the bioremediation area. The impact of the evaporation on the physicochemical parameters before and after Heglig oilfield bioremediation was tested with the statistical t-test, where P > 0.42 advocates no significant difference due to evaporation.

WAWQI is created by using the measurement of some important physicochemical variables of the produced water (Table 3). The WAWQI for Heglig oilfield produced water after the bioremediation was reported as poor, while the water before the bioremediation for Heglig oilfield and Neem oilfield represented very poor water quality, as shown in Table 3. When comparing the three sites according to WAWQI, it can be seen that Heglig oilfield after the bioremediation was the site that had the best water quality due to the parameters of oil content and COD was significantly affected by bioremediation followed by Heglig oilfield before the bioremediation, while Neem oilfield was the more contaminated site. Higher levels of total hardness, alkalinity, pH, TDS, electrical conductivity, and phenol due to evaporation of the water after the bioremediation did not significantly affect water quality.

Concentration of the 17 elements: Ag, Al, As, Ba, Be, Cd, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Se, Ti, V, and Zn from Heglig and Neem oilfields produced water samples were determined (Table 4). Six out of 17 elements exceeded RPEPIS guidelines in produced water of Neem oilfield. Pb, Ti, and Ag were found in produced water of Neem with very high concentrations, which was much higher than RPEPIS guidelines, while Al, Ba, and Cd were slightly higher than RPEPIS guidelines. According to Ocean ESU (2005), the heavy metals' concentration in the background soil of the Neem produced water pond was within the standard limits, however, the presence of excessive amounts of Pb, Al, Cd, Ag, Ti, and Ba confirms the impacts of Neem produced water. Concentrations of elements in produced water before the Heglig bioremediation were all within the RPEPIS guidelines. Four out of 17 elements (Al, As, Fe, and Ti) exceeded RPEPIS guidelines in produced water of Heglig oilfield after the bioremediation. The impact of evaporation on the heavy metals of Heglig oilfield produced water before and after the bioremediation was tested with the statistical t-test, and the analysis showed P > 0.09, which statistically advocates no significant difference due to evaporation. The water quality indices based on trace metals were used to assess the quality of the produced water according to RPEPIS guidelines. The HEI shows that Heglig oilfield produced water before the bioremediation was classified as low pollution, and medium pollution after the bioremediation. The produced water in Neem oilfield was classified as high pollution according to the HEI. The HPI was very high for Neem produced water, in the category of very poor. The quality ratings of Heglig oilfield produced water before and after bioremediation were excellent and good, respectively, according to HPI. However, when comparing our results for the three locations, it must be pointed out that Heglig oilfield before the bioremediation was the site that had the best water quality, followed by Heglig oilfield after bioremediation, while Neem oilfield was the site most contaminated by heavy metals.

The above indices are designed to consider different attributes in the water quality for water assessment. Even though the WAWQI considers the wider impacts of pollution on the water quality, it neglects the toxicity of metals present in the water. Likewise, HPI and HEI do not consider the toxicological impacts of the nutrients and physicochemical parameters. To overcome this problem a separate index, CCME WQI, is used in this work (Table 5). The descriptive statistics of 27 physicochemical and heavy metal parameters of produced water were calculated by CCME WQI, as shown in Table 5. Ten out of 27 variables exceeded RPEPIS guidelines in the produced water of Neem oilfield, which is classified as being of marginal quality. According to CCME WQI, the concentrations of Pb, Al, Cd, pH, total hardness, and TDS have increased by less than ten times the standard limits while the values of radioactivity, alkalinity, and TSS have increased between ten and 25 times the standard limits in Neem oilfield produced water. The concentration of Ag in Neem produced water has digressions in excess of 25 times RPEPIS guidelines. According to CCME WQI, Heglig oilfields produced water before and after bioremediation were classified as fair. Four variables (oil in water, COD, TSS and As) have increased by less than ten times over the RPEPIS guidelines for Heglig oilfield produced water before bioremediation. Seven variables (Al, As, Fe, pH, TDS, TSS, and Ti) appear in high concentrations for Heglig oilfield produced water after bioremediation and have increased by less than ten times the RPEPIS guidelines. In Neem oilfield produced water, the concentrations of TDS, alkalinity, Ag, Al, and Pb were in the category of severe potential irrigation problem according to FAO guidelines for evaluation of water quality for irrigation (Ayers & Westcot 1985). This confirms the scarcity of flora in the area around the evaporation ponds in Neem oilfield, unlike other areas that are not affected by the produced water. It is clear that there are differences in the values of HPI, HEI, WAWQI, and CCME WQI for samples of Heglig oilfield produced water before and after the bioremediation (Tables 3–5). This variation is due to the increase in the concentration of some sample metals after the bioremediation, which was a result of cumulative effect in the evaporation ponds. More detailed consideration of the radioactivity should be included in subsequent studies for Neem produced water. Field trials and study of heavy metal treatment by the phytoremediation technique are needed in future studies for Neem and Heglig produced water.

The study shows that the produced water of Neem oilfield exhibits high radioactive levels, high concentration of heavy metals like Pb, Al, Cd, Ag, Ti, and Ba, and high measurement of total hardness, pH alkalinity, TDS, electrical conductivity, and TSS. The HEI placed Neem oilfield produced water in the high contamination level, while HPI, on the other hand, considered it very poor quality. According to WAWQI and CCME WQI, the produced water quality of Neem oilfield was assessed as very poor and marginal, respectively. The trace metal concentrations in produced water before the Heglig bioremediation were within the standard limit, while concentrations of oil content, COD, TSS, and electrical conductivity were slightly high than the standard limit, which meant the produced water in Heglig oilfield before bioremediation was of fair quality and a low level of heavy metal pollution. The water quality of Heglig oilfield after the bioremediation was better than before the bioremediation due to the parameters of oil content and COD being significantly affected by the bioremediation. Higher levels of total hardness, alkalinity, pH, TDS, electrical conductivity, and phenol at Heglig oilfield after the bioremediation did not significantly affect water quality. More studies for treatment technology that can enhance the produced water quality after the bioremediation are highly required, mainly for heavy metal treatment. Furthermore, analysis for Neem produced water should be conducted to find suitable treatment technologies and avoid the nonconformance results.