Optimizing Thermal – Chemical Enhanced Heavy Oil Recovery in the Niger-Delta: An Experimental and Economic Approach

Introduction

Methodology

Experimental Methodology

Experimental Results

Core Analysis Results

Table 1 and Table 2 gave us a summary of the physical properties of the core samples, which were analysed, giving a wider understanding of the behaviours of the fluids to be injected and stored in the core samples. The core samples were seen to have low porosity and permeability values, which is in sync with published data on the characteristics of heavy oil reservoir rocks. The Rock lithology and thermal conductivity was estimated from standard density correlations.

Fluid Analysis Results

Table 3 and Table 4 tell us the characteristics of the heavy oil sample that was analysed, spanning from the density to the dynamic viscosity. The heavy crude oil sample was seen to have an API gravity of 16.79^oAPI and a dynamic viscosity of 438.02 cp, suggesting that it did not fall under the extra heavy oil classification, and corresponds with the known ranges of the Niger-Delta heavy crude properties.

i. Crude Oil Results:

Table 3. Crude oil calculated Density.

Table 3. Crude oil calculated Density.

Sample Name	Empty DB weight (g)	DB + Water weight (g)	DB + Crude oil weight (g)	Relative Crude Density	Crude API Gravity (oAPI)
Crude oil	22.89	79.42	76.83	0.9542	16.79

Legend: DB = Density Bottle (Pycnometer).

i. EOR Fluids Properties Results:

Table 4. Crude oil Viscosity and pH.

Table 4. Crude oil Viscosity and pH.

Sample Name	Temp $(\mathit{℃}$)	Efflux Time (s)	Viscometer constant	Density (g/cc)	${\mathit{\mu }}_{\mathit{k}}$ (cSt)	${\mathit{\mu }}_{\mathit{D}}$ (cP)	pH
Crude Oil	29	12606	0.0364149	0.9542	459.046	438.022	6.5

Table 5and Table 6 gives the physical properties of the chemicals used for the hot fluid flooding and further gives the relationship between the chemical fluid properties and potential oil productivity. A fairly direct correlation was observed between the fluid’s density and its dynamic viscosity. Waterflooding wasn’t conducted for the heavy oil sample recovery due to its high density.

Crude Oil Recovery Results

A. 50oC Thermal – Chemical Hybrid Flood (Core A)

This section gives the results of the total flooding process from imbibition to tertiary flooding when the chemical EOR fluid was heated to 50^oC and the utilized core sample was Core A. Secondary recovery wasn’t conducted due to the density and viscosity of the crude oil sample. During the tertiary flood process, an overburden pressure of 1500 psi was used, and 1000 ml of hot chemical was introduced into the accumulator.

Table 7. Core Flood results (50^oC Heat addition).

Table 7. Core Flood results (50^oC Heat addition).

							Tertiary Recovery
Sample Name	BP $\left(\mathit{℃}\right)$	FR (ml/min)	$∆\mathit{P}$ (psi)	PV (cc)	OOIP (cc)	${\mathit{S}}_{\mathit{w}\mathit{i}}$	Oil Recovered (ml)	RE (%)
DLS (core B)	86	75.00	0.46	12.84	9.42	3.42	7.80	82.76
Dry Gin	84	75.70	0.43	13.92	9.87	4.05	9.07	91.89
SLE	86	74.03	0.47	13.92	9.92	4.00	8.53	85.99
DPFA	86	50.50	0.51	13.92	9.87	4.05	8.31	84.19
BLE + E	83	62.30	0.46	13.92	9.89	4.03	9.08	91.81
XG	85	61.07	0.57	13.92	9.85	4.08	9.35	94.97

Figure 3. Graph of OOIP and Oil Recovery for the Fluid samples at 50$\mathrm{℃}.$

Figure 3. Graph of OOIP and Oil Recovery for the Fluid samples at 50$\mathrm{℃}.$

Figure 4. Recovery Efficiency of fluid samples in Figure 4.1.

Figure 4. Recovery Efficiency of fluid samples in Figure 4.1.

B. 80oC Thermal – Chemical Hybrid flood (CORE A)

This section gives the results of the total flooding process from imbibition to tertiary flooding when the chemical EOR fluid was heated to 80oC and the utilized core sample was Core A. Secondary recovery wasn’t conducted due to the density and viscosity of the crude oil sample. During the tertiary flood process, an overburden pressure of 1000 psi was used, and 1000 ml of hot chemical was introduced into the accumulator.

Table 8. Core Flood results (80^oC Heat addition).

Table 8. Core Flood results (80^oC Heat addition).

							Tertiary Recovery
Sample Name	BP $\left(\mathit{℃}\right)$	FR (ml/min)	$∆\mathit{P}$ (psi)	PV (cc)	OOIP (cc)	${\mathit{S}}_{\mathit{w}\mathit{i}}$	Oil Recovered (ml)	RE (%)
DLS (core B)	86	95.00	0.56	13.92	10.02	3.90	9.25	92.31
DG	84	95.69	0.55	13.92	9.89	4.03	9.53	96.36
SLE	86	96.24	0.57	13.92	9.84	4.08	9.16	93.04
DPFA	86	61.60	0.60	13.92	9.83	4.09	9.10	92.57
BLE + E	83	83.00	0.56	13.92	9.86	4.06	9.09	92.19
XG	85	60.38	0.66	13.92	9.92	4.00	9.71	97.89
DG + DPFA	85	82.17	0.59	13.92	9.89	4.03	9.56	96.69

Figure 5. Graph of OOIP and Oil Recovery for the Fluid samples at 50$\mathrm{℃}.$

Figure 5. Graph of OOIP and Oil Recovery for the Fluid samples at 50$\mathrm{℃}.$

Figure 6. Recovery Efficiency of fluid samples in Figure 4.3.

Figure 6. Recovery Efficiency of fluid samples in Figure 4.3.

Figure 7. 80^oC vs 50^oC Chemical injection Oil Recovery efficiency comparison.

Figure 7. 80^oC vs 50^oC Chemical injection Oil Recovery efficiency comparison.

From the thermal-chemical flooding results, at 50oC, dissolved liquid soap was seen to be the worst-performing fluid out of the six fluids tested, and Xanthan gum, which works on the mobility ratio reduction mechanism, was seen to be the best-performing fluid. When the heat level was increased to 80oC, Xanthan gum also performed the best, followed closely by the the alkali-surfactant mix, and the bitter-leaf extract concentration slightly performed the worst, with 92.19% oil recovery. This gives insights into the potential capabilities of these hot fluids in recovering a substantial amount of heavy crude from the reservoir.

C. Steam Flood Results (Core A)

This section gives the injected steam properties, and the oil recovery results as a result of Steam flooding through the core sample A.

Table 9. Injected Steam Properties.

Table 9. Injected Steam Properties.

Steam Injection Pressure (psi)	Steam Injection Temp. (oC)	Steam Injection rate (ml/min)	Steam Quality (%)	Heat of Steam (btu/lb)	Heat Injection Rate (btu/hr)
100	120	135	60	850	14320.80

Table 10. Steam Flood results.

Table 10. Steam Flood results.

Fluid Name	Temp (oC)	FR (ml/min)	$∆\mathit{P}$ (psi)	PV (cc)	OOIP (cc)	${\mathit{S}}_{\mathit{w}\mathit{i}}$	Oil Recovered (ml)	RE (%)
Hot Water	50	79.00	0.49	13.92	9.92	4.00	6.94	69.96
Hot Water	80	115.00	0.51	13.92	9.83	4.09	7.37	74.97
Steam	120	135.00	0.56	13.92	9.86	4.06	9.66	97.97

Figure 8. Graph of OOIP and Oil Recovery for varying hot water/steam temperatures.

Figure 8. Graph of OOIP and Oil Recovery for varying hot water/steam temperatures.

Steam flooding was seen to give poor results compared to hot chemical flood, when analyzing the recovery at 50oC and 80oC, and also incurred the highest energy costs, which would affect the overall economic balance of the project. The overall study shows that the thermal-chemical flood system is a more economical alternative to the conventional steam flooding system as it provides a higher recovery factor than steam (hot water) flooding at lower temperatures and with closely related operating costs.

Fluid Injection Economic Analysis

Steam Injection Economic Analysis

Four economic indicators that would be employed in the analysis are:

i.

Net Present Value (NPV)

ii.

Net Present Value (NPV)

iii.

Net Present Value (NPV)

iv.

Net Present Value (NPV)

Key Assumptions:

i.

1 barrel of oil = $50

ii.

The theoretical Heavy Oil field, has an OOIP of 5,000,000bbl.

iii.

1BTU of energy = $0.0075154.

iv.

$1 = 891.04 NGN.

v.

A strong linear correlation between experimental prototypes production rate and on-field production rates

vi.

A production duration of 1 year.

vii.

Field scale steam flow rate (M) of 2917 kg/hr.

viii.

Energy content of a 150L (85% Butane, 15% Propane) LPG (E) = 4,064,440 BTU.

iv.

150 Liters of LPG (85% Butane, 15% Propane) = 75kg.

Table 11. Cost Analysis of the fabricated local Boiler (8.5 Litres).

Table 11. Cost Analysis of the fabricated local Boiler (8.5 Litres).

	Steam Line	Valves	Thermometer	Pressure Gauge	Vessel	Furnace	Total
CAPEX ($)	15.21	8.34	17.20	11.22	50.13	35.02	137.12

Local Steam Boiler (Field scale) Economic Analysis

The Dataset used in developing upscaled Table 12 was obtained from Table 11 (laboratory scale). Analysis was done over a 1-year duration.

Table 12. Hot water/Steam flood economic analysis.

Table 12. Hot water/Steam flood economic analysis.

T (oC)	OOIP (bbl)	OP (bbl)	RR Bopd	GR ($)	LSG CAPEX ($)	COE ($)	REV ($)
50	5 million	762,277	2087	38,113,850	399,979	110,746	37,603,125
80	5 million	1,108,169	3034	55,408,450	399,979	170,865	54,837,606
120	5 million	1,302,116	3565	65,105,800	399,979	189,850	64,515,971

Figure 9. Graph of RE & COE for varying hot water/steam temperatures.

Figure 9. Graph of RE & COE for varying hot water/steam temperatures.

Equations corresponding with the columns in Table 4.24:

$$\mathit{O}\mathit{P}=RR\left({\displaystyle \frac{bbl}{day}}\right)*365$$

(3.11)

$$\mathit{R}\mathit{R}=Q\left({\displaystyle \frac{ml}{min}}\right)\mathrm{*}{\displaystyle \frac{1440}{\mathrm{158,987}}}\left({\displaystyle \frac{min.bbl}{ml.day}}\right)\mathrm{*}2917$$

(3.12)

$$\mathit{R}\mathit{R}=Q\left({\displaystyle \frac{ml}{min}}\right)\mathrm{*}{\displaystyle \frac{1440}{\mathrm{158,987}}}\left({\displaystyle \frac{min.bbl}{ml.day}}\right)\mathrm{*}2917$$

(3.13)

$$\mathit{L}\mathit{S}\mathit{G}\left(\mathbf{\$}\right)={\displaystyle \frac{M\left(\frac{kg}{hr}\right)\mathrm{*}Cs\left(\mathrm{\$}\right)}{m\left(\frac{kg}{hr}\right)}}$$

(3.14)

where M = Field scale steam flow rate (kg/hr)

Cs = Lab scale local steam generator cost ($)

m = lab scale steam flow rate (kg/hr)

m = 1kg/hr (from experimental analysis)

$$\mathit{L}\mathit{S}\mathit{G}={\displaystyle \frac{2917\mathrm{*}132}{1}}=\mathrm{\$}\mathrm{399,979}$$

(3.15)

$$\mathit{C}\mathit{O}\mathit{E}\left(\mathbf{\$}\right)={\displaystyle \frac{Q\left(BTU\right)}{E}}\mathrm{*}N\left({\displaystyle \frac{\mathrm{\$}}{75kg}}\right)$$

(3.16)

$$\mathit{Q}\left(\mathit{B}\mathit{T}\mathit{U}\right)=\left(M\left({\displaystyle \frac{kg}{hr}}\right)\mathrm{*}t\left(hr\right)\mathrm{*}4.2\left({\displaystyle \frac{kg}{kg.k}}\right)\mathrm{*}dt\left(K\right)\right)\mathrm{*}0.948\left({\displaystyle \frac{BTU}{KJ}}\right)$$

(3.17)

Q is the cumulative energy produced (in BTU) over a duration t (hr).

E is the energy content of the field scale LPG powered furnace (150 L) = 4,064,440 BTU.

N is the prevailing market price of 75kg LPG in ($ / 75kg).

At an average gas price of NGN 1,500 / kg, we can estimate that the energy cost is about NGN 6.696 / BTU ($0.0075154/BTU).

$$\mathit{R}\mathit{E}\mathit{V}\left(\mathbf{\$}\right)=GR-\left(LSG+COE\right)$$

(3.18)

Further Analysis at the Threshold Temperature of 73$\mathit{℃}$For the economical steam injection threshold of 73^oC, the present values at various discounted rates for the 1year duration was analysed, and the DCF-ROR was estimated.

Table 13. Optimal Temperature Economic Analysis.

Table 13. Optimal Temperature Economic Analysis.

Temp (oC)	Oil Flowrate (bpd)	Revenue ($)	2% ($)	50% ($)	100% ($)
73	2817.82	51,460,438	50,451,410	34,306,959	25,730,219

P/$ = ${\displaystyle \frac{\mathrm{51,460,438}}{570844}}$ = 90.15 (Expenses other than the total cost of steam generation was not factored).

Payout time = $0+ {\displaystyle \frac{\mathrm{570,844}}{\mathrm{30,711,856}}}$ = 0.01859 years (6.764 days). (Other expenses not factored in).

The values gotten show that the cost of the local steam boiler was a little fraction compared to the value of heavy oil that is estimated to be obtained from the technique (2817.82 bpd) at the economic decision temperature, 73^oC.

Chemical Fluid Injection Economic Analysis

- Alkali – Surfactant Flooding @73$℃$

Key Assumptions:

i.

1 barrel of oil = $50.

ii.

The theoretical Heavy Oil field, has an OOIP of 5,000,000bbl.

iii.

1BTU of energy = $0.0075154.

iv.

$1 = 891.04 NGN.

v.

Local market prices of agricultural feedstock as at march 2024.

vi.

A strong linear correlation between experimental prototypes production rate and on-field production rates.

vii.

A production duration of 1 year.

viii.

Field scale magnification of 2917.

ix.

Energy content of a 150L (85% Butane, 15% Propane) LPG (E) = 4,064,440 BTU.

x.

150 Liters of LPG (85% Butane, 15% Propane) = 75kg.

xi.

Cost of a 1% vol – vol DG + DPFA (surfactant – alkali) solution in distilled water (1L) = $0.1.

xii.

Cost of a 75kg LPG = $126.23 ($1.68/kg)

Estimated specific heat capacity of the mixture (mathematical analysis)

SHC of Water = $4.18{\displaystyle \frac{J}{g℃}}$

SHC of Ethanol + Palm frond ash = $2.46{\displaystyle \frac{J}{g℃}}$

Density (Water, DG+DPBA) = (1, 1.07009)${\displaystyle \frac{g}{ml}}$

Mass of a 10ml DG+DPBA in 1000ml Water = 1010.7009g

Mass fraction of water = ${\displaystyle \frac{1000}{1010.7009}}=0.9894$

Mass fraction of DG + DPBA = ${\displaystyle \frac{10.7009}{1010.7009}}=0.0106$

Weighted SHC = (0.9894*4.18) + (0.0106*2.46) = 4.162${\displaystyle \frac{J}{g℃}}$

Cost of Energy Estimation ($)

From equation 4.17, $\mathit{Q}\left(\mathit{B}\mathit{T}\mathit{U}\right)=\left(M\left({\displaystyle \frac{kg}{hr}}\right)\mathrm{*}t\left(hr\right)\mathrm{*}4.162\left({\displaystyle \frac{kg}{kg.k}}\right)\mathrm{*}dt\left(K\right)\right)\mathrm{*}0.948({\displaystyle \frac{BTU}{KJ}}$)

For a 1year duration;

$Q \left(labscale\right)= 1.07009{\displaystyle \frac{g}{ml}}*82.17{\displaystyle \frac{ml}{min}}*1{\displaystyle \frac{kg}{1000g}}*8760{\displaystyle \frac{hr}{yr}}*4.162{\displaystyle \frac{kg}{kg. k}}\left(73-30\right)k* 0.948{\displaystyle \frac{Btu}{kj}}=130682.24 Btu$.

$Q \left(fieldscale\right)=130682.24*2917=\mathrm{381,200,094.08} Btu.$

Number of gas cylinders requirement (75kg) = ${\displaystyle \frac{381200094.08}{4064440}}=$937.9.

Cumulative LPG cost = $937.9*126.23\left({\displaystyle \frac{\$}{75kg}}\right)=$ $118,391.12

CAPEX = $399,979.

$\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{C}\mathrm{o}\mathrm{s}\mathrm{t}\mathrm{o}\mathrm{f}\mathrm{E}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y}=\$\mathrm{518,370.12}.$

Net Revenue Estimation ($)

$Oil Flowrate \left(fieldscale\right)=3170bopd$.

$Gross Revenue \left(one year\right)=3170{\displaystyle \frac{bbl}{day}}*365.25{\displaystyle \frac{days}{year}}*1year*50{\displaystyle \frac{\$}{bbl}}=\$\mathrm{57,892,125}$

$Cost of Energy=\$\mathrm{518,370.12}$

$Cost of Material=0.0001{\displaystyle \frac{\$}{ml}}*82.17{\displaystyle \frac{ml}{min}}*525960{\displaystyle \frac{min}{year}}*1year=\$4321.82$

$Net Revenue \left(one year\right)=\mathrm{57,892,125}-\left(\mathrm{518,370.12}+4321.82\right)=\$\mathrm{57,369,433.06}.$

The net revenue from hot DG + DPBA flooding at 73$℃$(significant threshold) supersedes the net revenue from hot water flooding alone (@73$℃$) by about 11.48%, thus implying a more profitable investment for heavy oil production.

Conclusion

The experimental analysis and economic evaluation of various enhanced oil recovery (EOR) methods highlight the superior performance and cost-effectiveness of hot chemical EOR compared to steam flooding for heavy oil recovery. The key findings are summarized as follows:

1. Hot chemical EOR proved to be a more economical alternative to steam flooding, primarily due to lower energy requirements and higher efficiency at lower temperatures.

2. Steam flooding showed an exponential increase in energy costs for linear production increments, making it less economically viable.

3. The optimal temperature for hot water flooding was identified as 73°C, with 90+% of the tested hot chemicals having better recoveries at that temperature.

4. The amount of residual oil left post-flooding was independent of the initial oil saturation and viscosity, indicating the robustness of the hot chemical EOR process.

5. More viscous hot chemicals yielded the highest recovery values, emphasizing the importance of chemical properties in EOR.

6. The rate of heavy oil production in hot chemical flooding was primarily influenced by the injection rate, pressure, temperature, chemical properties, and rock petrophysical properties.

7. A net revenue increase of approximately 11.48% was achieved with DG + DPBA flooding compared to hot water alone, at the economic temperature of 73°C.

Acknowledgement: A heartfelt appreciation is reserved for God almighty, for his inspiration and guidance throughout the course of this research study. I also wish to appreciate the University of Port Harcourt, Nigeria, for their technical support during the conduction of the experimental analysis. My heartfelt appreciation is also extended to the editorial team of Improved Oil and Gas Recovery Journal, for their top-tier suggestions, in order to obtain a high-quality research paper.

Conflicting Interests: The Author declares that he has no conflicting interests.

Nomenclature

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