Surfactant EOR · HTHS carbonates

Retention Economics — Surfactant EOR Screening Model

An interactive discounted-cash-flow screening model that resolves surfactant dynamic retention, Γ, into project value for chemical flooding in high-temperature, high-salinity carbonate reservoirs. The retention–recovery relation is fitted to twelve screened HTHS corefloods and is applied only inside the calibrated window Γ = 0.083–0.33 mg/g-rock. At the scenario specified in Section 2 the model returns NPV = —, an internal rate of return of —, a breakeven retention Γ* = —, and a breakeven oil price of —. Chemical spend is fixed by slug design and not by retention, so each additional milligram retained per gram of rock removes incremental barrels while the injected chemical cost holds constant.

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NPV

—

IRR · vs d_r hurdle

—

Unit tech. cost

—

Breakeven retention Γ*

Interactive companion to the manuscript Techno-economic Screening of Surfactant Flooding in High-Temperature, High-Salinity Carbonates under Retention Uncertainty — under review at Petroleum Research (KeAi Publishing).

MANUSCRIPT PDF DATA WORKBOOK

HOW TO USE

What this is: An interactive implementation of the screening model developed in the accompanying manuscript (under review at Petroleum Research), downloadable from the link in the header. The page loads on the manuscript base case — fitted retention–recovery relation, Γ = 0.200 mg/g-rock, oil price $60/bbl.
Parameters: Every input lives in the Scenario parameters pane. Change one and each figure, the abstract values, and the live readout recompute against the edited scenario.
Recovery-factor basis: The fitted relation RF_lab = A·e^−kΓ is the default and holds only over Γ = 0.083–0.33 mg/g-rock. Manual RF input substitutes an entered value for scenario testing; recovery then decouples from Γ and breakeven retention reads n/a. Sweep efficiency and the saturation ratio scale RF_lab to field basis in both modes.
Figures are interactive: Hover for exact values, drag to zoom, double-click to reset the axes, and use the camera icon to download a PNG. Figures re-render as parameters move.
Export and reset: Export scenario downloads a text file of all inputs and computed outputs. Reset base case restores the defaults.
Where things are: Parameters in the Scenario parameters pane, results figures in the Results panes, assumptions and limitations in the Assumptions and limitations pane.

Scenario recordmodel-equations workbook · 2026

Prepared by	Imad A. Adel
Subject	Surfactant EOR · HTHS carbonates
Basis	n = 12 corefloods · calibrated Γ 0.083–0.33 mg/g · 2026
Scenario status	BASE CASE

Summary of results — current scenariobase case

NPV

—

IRR

—

vs d_r hurdle

Incremental oil

—

Unit tech. cost

—

Payback

—

discounted, interpolated

Breakeven retention Γ*

—

Section 01 · Basis and benchmark

Basis and benchmark

A discounted-cash-flow screening model that maps surfactant dynamic retention (Γ) directly to project value for chemical flooding in high-temperature, high-salinity carbonate reservoirs. Calibrated on a screened benchmark of twelve HTHS corefloods, it resolves the retention, oil-price, and sweep thresholds at which NPV crosses zero.

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Stage A — Recovery

Twelve screened HTHS carbonate corefloods (SP and ASP, 78–100 °C, up to 243,000 ppm TDS) collapse onto a single exponential decay of recovery with dynamic retention, scaled to field conditions through sweep efficiency and the saturation ratio.

Stage B — Cash flow

Chemical spend is set by slug design (ASP + two polymer drives), not by retention — so every extra milligram retained erodes barrels while cost stays fixed. A five-year uniform cash flow is discounted at 10% against upfront capital.

Stage C — Thresholds

Bisection root-finding resolves the breakeven retention, breakeven oil price, and sweep-efficiency threshold where value crosses zero, and one-at-a-time sensitivity ranks the engineering levers that move NPV the most. At the current scenario Γ* solves NPV(Γ*) = 0 at —.

Coreflood benchmark — screened HTHS carbonate dataset (n = 12)Γ 0.083–0.33 mg/g

Screened HTHS carbonate coreflood benchmark: retention, laboratory recovery, formulation, core type, temperature and total dissolved solids.
#	Γ mg/g	RF %S_orw	Form.	Core	T °C	TDS ppm

Fig. 1 — Coreflood benchmark & retention-decay fitn = 12 · R² = 0.89

Fig. 1 — Coreflood benchmark & retention-decay fit. Laboratory recovery (% S_orw) against dynamic retention for the screened HTHS carbonate dataset: circles are ASP corefloods, diamonds are SP corefloods, and the solid curve is the fitted exponential RF_lab = A_RF·e^−k_RF·Γ evaluated at the coefficients of Section 2. The shaded band marks the calibrated domain Γ = 0.083–0.33 mg/g-rock; the open marker is the current operating retention. n = 12 · R² = 0.89

Governing equationsmodel-equations workbook · 2026

Calibrated domain. The exponential RF fit is empirical and valid only within the calibrated retention range (0.083–0.33 mg/g-rock); those two values are the minimum and maximum dynamic retentions in the screened dataset. Evaluations outside that interval are extrapolations of the fitted relation and carry no coreflood support. The model flags any such evaluation in Section 2 and on the incremental-oil readout.

Section 02 · Scenario parameters

Scenario parameters

The specification below opens at the base case of the model-equations workbook (2026). Every field is editable, and each figure, table and readout on this page recomputes from these values. Retention Γ, volumetric sweep E_v and oil price are the screening variables and carry sliders; the remaining fields are entered numerically. Pressure, temperature and salinity enter only through the coreflood screen, not as model inputs.

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Screening variables — primaryΓ mg/g-rock · E_v fraction · $/bbl

Recovery-factor basis

RF_lab manual %S_orw

Dynamic retention Γ0.200 mg/g

0.05calibrated 0.083–0.330.40

Volumetric sweep E_v0.55

0.40breakeven ≈ —0.75

Oil price P_oil$60/bbl

35constant price over project life95

2.1 · Screening variables

Parameter	Value ✎	Unit
Dynamic retention Γ		mg/g-rock
Volumetric sweep E_v		fraction
Oil price P_oil		$/bbl

2.2 · Reservoir and recovery

Parameter	Value ✎	Unit
Bulk volume		MMbbl
Porosity φ		fraction
Initial oil saturation S_oi		fraction
Formation volume factor B_o		rb/stb
Saturation ratio S_orw/S_oi		fraction
RF coefficient A_RF		% S_orw
Decay coefficient k_RF		g/mg

PV = — MMbbl · OOIP = — MMstb

2.3 · Chemical slug designwt% · ppm · PV

Slug	Size ✎	Surfactant ✎	Alkali ✎	Co-solvent ✎	Polymer ✎
ASP slug
Polymer drive 1
Polymer drive 2

Stage cost / bbl injected — ASP — · PD1 — · PD2 — USD

2.4 · Chemical unit pricesUSD/lb

Parameter	Value ✎	Unit
Surfactant		USD/lb
Polymer		USD/lb
Co-solvent		USD/lb
Alkali		USD/lb

2.5 · Economic frame

Parameter	Value ✎	Unit
CAPEX		MMUSD
Discount rate d_r		%
Production OPEX		$/bbl
Injection OPEX c_inj		$/bbl
Injection factor f_inj		× PV
Project life T		yr
Fluid density ρ_w		lb/bbl

Section 03 · Recovery and cash flow

Recovery and cash flow

At Γ = — mg/g-rock the fitted relation returns RF_lab = — % S_orw and RF_field = — % OOIP. Applied to an OOIP of — MMstb this gives ΔN_p = — MMstb and gross revenue of — at —. Chemical, injection and production operating cost total —; CAPEX of — is charged at year zero. The uniform annual cash flow of — over — years discounts at — to NPV = —.

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Fig. 2 — Discounted cash flow profile$MM · discounted

Fig. 2 — Discounted cash flow profile. Bars are annual discounted cash flow in $MM, the line is cumulative discounted cash flow, and the dotted vertical marks the discounted payback intercept obtained by linear interpolation between the bracketing years. Year 0 carries CAPEX as a lump sum.

Fig. 3 — Value composition — revenue to NPV$MM · pre-tax · constant 2026 USD

Fig. 3 — Value composition — revenue to NPV. Gross revenue is reduced in sequence by chemical cost, injection operating cost, production operating cost, the discounting term, and CAPEX; the closing bar is NPV. All quantities in $MM, pre-tax, constant 2026 USD.

Section 04 · Retention economics

Retention economics

Chemical mass injected is set by slug size and concentration and does not vary with Γ. Retention therefore acts only on the recovery term, and NPV falls monotonically with Γ at fixed slug design. The crossing point is resolved by bisection on Γ ∈ [0.01, 1.0] mg/g-rock to a tolerance of 10⁻⁸.

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Fig. 4 — Project value and rate of return against dynamic retentionshared retention axis

Fig. 4 — Project value and rate of return against dynamic retention, shared retention axis. Panel (a) is NPV in $MM, filled to the zero line; panel (b) is the internal rate of return in per cent, capped at 120%. Both panels sweep Γ = 0.05–0.40 mg/g-rock with every other parameter held at the Section 2 specification. The vertical rule crossing both panels is the breakeven retention Γ* at which NPV = 0; the open markers are the current scenario.

Breakeven retention

At — the breakeven retention is Γ* = —. The scenario operates at Γ = — mg/g-rock, —

Section 05 · Viability map

Viability map

The response surface is evaluated on a 55 × 55 grid spanning Γ = 0.05–0.40 mg/g-rock and oil price 35–95 $/bbl, with every other parameter held at Section 2. The zero contour separates the viable and uneconomic domains and is the locus of the Γ* and P* roots reported elsewhere on this page.

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Fig. 5 — NPV response surface — retention × oil price$MM · 55 × 55 grid

Fig. 5 — NPV response surface — retention × oil price. Filled contours of NPV in $MM over the retention–price plane; white contour = breakeven (NPV = 0) · marker = current scenario. Warm fill denotes negative NPV.

Section 06 · Risk

Risk

Each parameter is moved to its low and high bound in isolation while all others stay at the current scenario. Bounds are the manuscript uncertainty ranges. Bars are ordered by span, so the ranking is the ranking of parameter influence on NPV at this operating point and not a general ranking.

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Fig. 6 — One-at-a-time sensitivitymanuscript uncertainty ranges

Fig. 6 — One-at-a-time sensitivity — manuscript uncertainty ranges. Each bar spans the NPV obtained at the low and high bound of one parameter, drawn from the scenario base marked by the vertical rule. Red is the downside branch, petrol the upside branch.

Section 07 · Cost structure

Cost structure

Full-cycle expenditure is CAPEX plus chemical, injection and production operating cost. The chemical term is fixed by slug design; injection cost scales with pore volume and the injection factor; production cost scales with incremental oil. Cost per incremental barrel therefore rises with retention while total spend stays flat.

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Fig. 7 — Full-cycle cost structuremass-based chemical split · $MM

Fig. 7 — Full-cycle cost structure. Shares of full-cycle expenditure split by chemical component (mass-based), injection OPEX, production OPEX and CAPEX; the centre annotation is total full-cycle expenditure in $MM.

Fig. 8 — Chemical cost per incremental barrel vs retention$/bbl · Γ 0.05–0.35 mg/g-rock

Fig. 8 — Chemical cost per incremental barrel vs retention. Stacked component cost per incremental barrel across Γ = 0.05–0.35 mg/g-rock in 0.025 mg/g steps: fixed spend ÷ shrinking barrels.

Fig. 9 — NPV improvement waterfallengineering levers from current scenario

Fig. 9 — NPV improvement waterfall — engineering levers from current scenario. Sweep efficiency raised by 0.05 (capped at 0.90) and retention reduced by 0.10 mg/g-rock (bounded below at 0.05) applied in sequence from the current scenario; the closing bar is the optimized NPV.

Section 08 · Breakeven analysis

Breakeven analysis

The breakeven oil price is the root of NPV(P) = 0 solved by bisection on P ∈ [5, 300] $/bbl. The screening matrix reports model outputs at seven retentions spanning the calibrated range; the highlighted row is the retention nearest the current scenario.

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Fig. 10 — Breakeven oil price envelope vs retention$/bbl · Γ 0.05–0.35 mg/g-rock

Fig. 10 — Breakeven oil price envelope vs retention. Oil price at which NPV = 0 across Γ = 0.05–0.35 mg/g-rock (amber), chemical cost per incremental barrel (petrol, dashed) and the current oil price (dotted horizontal) for reference. The open marker is the breakeven price at the current retention.

Screening matrix — outputs across the calibrated retention rangeseven retentions · current scenario highlighted

Model outputs at seven retentions: field recovery factor, incremental oil, unit technical cost, breakeven oil price, internal rate of return and net present value.
Γ mg/g	RF_field %	ΔN_p MMstb	UTC $/bbl	BE price $/bbl	IRR %	NPV $MM

Section 09 · Assumptions and limitations

Assumptions and limitations

Prepared by Imad A. Adel · Senior Petroleum Research Engineer, Chemical & Petroleum Engineering

Assumptions and limitationspre-tax · constant 2026 USD