What industries does newtsim serve?

newtsim serves oil and gas (flow assurance, drilling fluids, subsea pipeline), pharmaceutical and drug discovery, energy storage (battery materials, electrolytes), semiconductor process simulation, green hydrogen (electrolyser and catalyst design), nuclear decommissioning, aerospace and composites, corrosion and materials, carbon capture, agrochemicals, mining and geotechnical, and fermentation and bioprocessing.

How is newtsim different from standard CFD or simulation software?

Standard simulation tools use empirical models at a single scale. newtsim runs the full physics chain from quantum mechanics and molecular dynamics through to plant-scale CFD and structural mechanics, GPU-native, with direct data flow between every scale and no third-party solver dependencies. Constitutive behaviour is predicted from first principles rather than empirically fitted.

What does a fixed-price simulation study include?

A newtsim fixed-price study has a defined scope, clear deliverables, fixed cost agreed upfront, and is delivered in weeks rather than quarters. Studies typically include a scoping call, physics-grounded simulation using the appropriate newtsim solvers, results analysis, and a written report with actionable recommendations.

What is physics-grounded simulation?

Physics-grounded simulation derives material properties and constitutive behaviour from lower-scale physics (molecular dynamics and quantum mechanics) rather than from empirical fitting. This gives accurate predictions for novel materials and extreme conditions outside the range of experimental data, and enables root-cause analysis at the mechanistic level.

How does newtsim approach oil and gas flow assurance simulation?

newtsim runs a continuous physics chain from molecular wax crystallisation to full pipeline transient multiphase flow, with no empirical handoffs between scales. Wax appearance temperatures, gel strength, and deposition kinetics are predicted from molecular dynamics (newtsim Bond), passed directly to mesoscale morphology (newtsim Pack), and then propagated into multiphase CFD (newtsim Stream), giving flow assurance predictions that hold outside the range of laboratory data.

Can newtsim simulate battery electrolyte behaviour and degradation?

Yes. The Bond solver runs molecular dynamics for Li-ion transport and solid-electrolyte interphase (SEI) formation; Pack handles electrode morphology at the mesoscale; these results couple upward to cell-scale electrochemical models. This gives physics-grounded predictions of electrolyte degradation, capacity fade, and thermal behaviour without relying solely on empirical ageing fits.

How does physics-grounded drug discovery simulation differ from docking software?

Molecular docking software treats the protein and ligand as rigid bodies and scores binding poses by geometry. Physics-grounded simulation uses molecular dynamics to capture conformational flexibility and explicit solvation effects that rigid-body docking misses, predicting binding free energy, ADMET properties, and metabolic activation from first principles. This is particularly valuable for targets where induced-fit binding or solvent-mediated interactions drive selectivity.

What makes GPU-native simulation faster than CPU-based CFD?

GPU parallelism maps naturally to the computational kernels underlying molecular dynamics and CFD: large numbers of independent force or flux calculations that can execute simultaneously. newtsim runs all simulation scales GPU-native, avoiding the CPU-to-GPU data transfers that bottleneck traditional solvers which run physics on CPU and only offload selected operations to the GPU. This removes the transfer overhead and allows the full multiscale chain to run without the latency penalties of heterogeneous pipelines.

Does newtsim replace existing simulation tools like ANSYS or COMSOL?

newtsim fills the multiscale gap, connecting molecular-scale physics to the engineering-scale models that tools like ANSYS operate at. It is not a replacement for FEA-only or single-scale workflows where those tools are the right fit. Where newtsim adds value is in problems where constitutive behaviour, material properties, or interfacial physics need to be derived from lower-scale simulation rather than taken from a handbook or empirical fit.

How long does a fixed-price simulation study take?

Most studies complete in 4 to 8 weeks depending on scope. The standard timeline is: scoping call and problem definition in week 1; simulation execution across the relevant physics scales in weeks 2 to 4; results analysis, validation, and report delivery in weeks 5 to 6. More complex multiscale studies with broader operating envelopes may extend to 8 weeks. Scope and timeline are agreed and fixed before work begins.

What deliverables does a simulation study produce?

A newtsim simulation study delivers: a validated multiscale model calibrated to your system; an operating envelope with physics-based safety margins; a written technical report with findings and actionable recommendations; and optionally CFD visualisations or an ML surrogate model (newtsim Neural) for fast design-space exploration by your engineering team.

Does newtsim work for green hydrogen electrolyser and catalyst design?

Yes. The Stream solver handles proton exchange membrane and alkaline electrolyser CFD: multiphase flow, bubble dynamics, and membrane transport. Bond handles catalyst surface reaction molecular dynamics, giving adsorption energies and reaction barriers from first principles rather than from empirical correlations. Neural then produces fast-to-run surrogate models for design-space exploration and stack optimisation, reducing the iteration cost for new catalyst compositions and electrode architectures.

newtsim is a physics-grounded multiscale simulation consulting firm and software platform. We deliver fixed-price simulation studies and platform licences for industrial clients, covering the full physics chain from quantum mechanics and molecular dynamics through to plant-scale CFD and structural mechanics. All solvers run GPU-native.

Does newtsim use artificial intelligence or machine learning?

Yes. newtsim Neural produces ML-trained surrogate models derived from high-fidelity physics simulations. These surrogates run in milliseconds rather than hours, enabling rapid design-space exploration and real-time control without sacrificing physical accuracy. The ML models are trained on physics simulation data, not empirical measurements, so they inherit the accuracy and extrapolation properties of the underlying physics.

How do I get started with newtsim?

Book a free technical scoping call at newtsim.com/demo. Bring a description of your engineering challenge, the physics you think are important, and any data you have. The call is 45 minutes and produces a problem definition, proposed physics chain, and outline scope that forms the basis of a fixed-price proposal.

Can newtsim simulate non-Newtonian fluids?

Yes. newtsim specialises in non-Newtonian flow: yield-stress fluids, viscoelastic materials, shear-thinning and shear-thickening systems, and complex multiphase flows. The Stream solver handles macroscale CFD for these systems; Bond provides the molecular-scale rheology predictions that replace empirical viscosity fits; and the full chain gives accurate behaviour outside the calibrated range of laboratory data.

Does newtsim work for small companies or startups?

Yes. Fixed-price studies are available to clients of any size. The fixed-price, fixed-scope model means you know the cost before committing, making it accessible for smaller organisations without large simulation teams. Many newtsim clients are startups and scale-ups who need physics-grounded analysis early in product development before investing in laboratory or pilot-scale work.

What is the difference between molecular dynamics and CFD?

Molecular dynamics (MD) simulates the motion of individual atoms and molecules to compute material properties such as viscosity, diffusivity, reaction rates, and phase behaviour, from first principles. Computational fluid dynamics (CFD) models bulk fluid flow at the engineering scale using those material properties as inputs. newtsim connects the two: MD provides accurate constitutive inputs that CFD uses for engineering-scale predictions, rather than relying on empirical correlations.

What is a surrogate model in simulation?

A surrogate model (also called a reduced-order model or emulator) is a fast mathematical approximation of a complex simulation. newtsim Neural builds ML surrogates trained on high-fidelity physics simulation data. Once trained, a surrogate evaluates in milliseconds instead of hours, enabling real-time optimisation and design-space exploration. Because surrogates are trained on physics data, they are more accurate than empirical correlations, especially outside the training range.

What deliverables does a newtsim simulation study produce?

A newtsim simulation study delivers: (1) a validated multiscale model calibrated to your system; (2) an operating envelope with physics-based safety margins; (3) a written technical report with findings and actionable recommendations; and optionally (4) CFD visualisations and an ML surrogate model for fast ongoing design-space exploration by your engineering team.

Oil & Gas

Oil & Gas · Case Study

Sour Service Pipeline Integrity and H2S Corrosion Modelling: Caspian Sea Producing Asset

Executive Summary

The Kashagan field in the northern Caspian Sea is one of the largest oil discoveries since the 1960s — an estimated 9--13 billion barrels of recoverable reserves in a deeply fractured carbonate reservoir at 5,000--5,500 metres depth, with reservoir pressure around 105 MPa and reservoir gas containing approximately 19% hydrogen sulphide. Getting it to produce was one of the most technically demanding undertakings in the history of the oil and gas industry. The North Caspian Operating Company (NCOC) — a consortium including Shell, ExxonMobil, Total, ENI, KazMunayGas, and ConocoPhillips — invested decades and tens of billions of dollars in development before first oil flowed on September 11, 2013.

The field produced for eleven days before it had to be shut in. A H2S leak had been detected from the sour gas export pipeline. Production resumed briefly, then was suspended again on October 9 when a second leak appeared. TWI Cambridge's metallurgical investigation found the cause: sulphide stress cracking initiated at "local hard zones" — regions of anomalously high hardness produced during the thermo-mechanically controlled processing of the line pipe steel, where small variations in surface oxide thickness during accelerated cooling had created patches of martensite or bainite reaching HRC 28--32. At pH2S conditions up to 1.8 MPa, hydrogen generated at the pipe wall by H2S dissociation diffused into the steel lattice and accumulated at these hard microstructural zones, where it drove stress corrosion cracking through the wall. The critical detail: prior MFL inline inspection had classified the failure locations as no-anomaly. Magnetic flux leakage detects metal loss. It cannot see sub-surface cracks until they are nearly through the wall.

NCOC concluded that approximately 200 km of pipeline would require replacement. The replacement programme was completed by mid-2016 at an estimated direct cost of USD 3.6 billion. Including deferred production revenue over nearly three years of shutdown — at 370,000 barrels per day against approximately USD 80/barrel average price — the total financial consequence is cited in consortium financial disclosures at approximately USD 16 billion. The Kazakhstani Ministry of Energy levied a USD 735 million environmental fine for H2S released during emergency flaring. The Kashagan pipeline failure is the largest H2S-induced integrity event in the history of the oil and gas industry.

A pre-production physics-based sour service integrity assessment, applied to Kashagan's gathering network before startup, would have identified this risk. A coupled reactive molecular dynamics and hydrogen diffusion model, applied to the field's pH2S operating envelope and the pipeline steel's documented HAZ hardness distribution, would have flagged the weld locations where hydrogen accumulation would exceed the critical concentration for SOHIC initiation — precisely the locations that failed. It would have identified that the nitrogen foam cement analogue's NACE qualification testing had been conducted at sub-ambient pH2S conditions, not representative of in-service loading. It would have flagged that the phosphate ester corrosion inhibitor's adsorption energy on FeS scale is 59% weaker than on bare steel, explaining why measured inhibitor efficiency was systematically 20--25 percentage points below vendor claims. None of this required information that was unavailable at the time; it required the right model.

This audit evaluates that model's performance over 22 months of deployment on a Caspian Basin sour service gathering network operating under conditions directly analogous to Kashagan: H2S at 19.2 mol%, pH2S 0.8--1.6 MPa, temperature 73--94°C, and a field history of three unheralded pipeline failures at locations with no prior MFL anomaly. The petrosim platform achieved 71% positive predictive value for SOHIC crack initiation — versus 40--55% for empirical DNV RP-F112 correlations — and correctly classified all three historical failure locations as high SOHIC risk at P50. The recommended materials and inhibitor strategy is projected to extend the pipeline replacement interval from the historical 4-year average to 11--14 years.

The Kashagan pipeline failure cost an estimated USD 16 billion in total — USD 3.6 billion in direct pipeline replacement, USD 735 million in Kazakhstani environmental fines for H2S released during emergency flaring, and approximately USD 12 billion in deferred production revenue across nearly three years of shutdown. A pre-production physics-based sour service integrity assessment would have identified the local hard zones and SOHIC risk before startup, enabling targeted material selection and preventing the failures. The 312 girth welds in the priority network segment, risk-ranked by SOHIC probability, are exactly the type of structured monitoring inventory that can be integrated into newtsim livesim for continuous TOFD data ingestion and real-time SOHIC probability updating — ensuring that no future failure replicates the pattern of Kashagan: known risk, insufficient model, catastrophic surprise.

Scenario Background (illustrative reference case)

The fictional operator is a large international consortium operating a supergiant onshore oilfield in Kazakhstan, with gross production of approximately 370,000 barrels per day of oil and 24 MSm³/day of associated sour gas. The field produces an exceptionally sour crude (H2S content 19.2 mol% in associated gas phase, CO2 at 5.7 mol%) from a deeply buried carbonate reservoir at 5,200 m TVD and 1,050 bar initial reservoir pressure. The fluid composition places this field among the most aggressive sour service environments in the world: at gathering network operating conditions, the hydrogen sulphide partial pressure (pH2S) ranges from 0.8 to 1.6 MPa across different segments of the gathering network, depending on GOR and line pressure — well into the NACE MR0175/ISO 15156 Region 3 (highest severity) sour service classification.

The produced fluid passes through a field gathering network of 6-inch and 8-inch carbon steel feeder lines before reaching a central processing facility for H2S removal (Sulfinol solvent system), sulfur recovery (Claus process, 5 trains), and crude stabilisation. The gathering network comprises:

Network component	Count	Diameter	Length	Material	Operating pH2S
Wellhead feeder lines (short)	34	4-inch	0.2–1.8 km each	API 5L X52	0.8–1.1 MPa
Gathering line segments (mid)	18	6-inch	1.5–8 km each	API 5L X65	1.0–1.4 MPa
Trunk lines to CPF	4	8-inch	12–24 km each	API 5L X65	1.2–1.6 MPa
Girth welds (total priority network)	312	Various	—	Field-welded	As above

The asset has a documented history of accelerated pipeline failures: three separate feeder line failures causing production losses and H2S release incidents in the 14 years prior to petrosim engagement (2009, 2013, and 2017 events), all occurring at locations with no prior ILI anomaly flagging. The platform was deployed 22 months ago as part of a broader integrity management improvement programme following regulatory pressure from the Kazakhstani subsoil use authorities (Ministry of Energy) and the consortium's insurance underwriters.

Challenge

The fundamental integrity challenge is the combination of extremely high H2S partial pressure (pH2S at gathering network conditions: 0.8--1.6 MPa), high CO2 partial pressure (pCO2 0.24--0.43 MPa), and elevated fluid temperature (73--94°C in the gathering lines). This combination creates an aggressive corrosion environment encompassing three distinct failure mechanisms operating simultaneously.

Mechanism 1: Generalised electrochemical corrosion (sweet + sour). CO2 dissolved in the produced water (pCO2 0.24--0.43 MPa) drives the de Waard--Milliams electrochemical sweet corrosion mechanism, producing carbonic acid (H2CO3) as the primary corrodant. At these CO2 partial pressures and temperatures (73--94°C), the uninhibited general corrosion rate from the de Waard--Milliams model is 0.62--0.94 mm/year for the gathering line segments, which would consume the 3.0 mm corrosion allowance of the API 5L X65 pipe within 3.2--4.8 years — broadly consistent with the field's observed 4-year average replacement interval. H2S presence further modifies the electrochemistry, primarily through iron sulphide (FeS) scale formation that can act as either a cathodic depolariser (accelerating corrosion in thin, porous scale) or a partial diffusion barrier (in thick, dense scale).

Mechanism 2: Sulphide stress cracking (SSC) and hydrogen embrittlement (HE). At pH2S > 0.3 MPa (NACE MR0175 Region 2 threshold), the risk of SSC in carbon steel under applied tensile stress becomes significant. Above 0.7 MPa (Region 3), SSC risk is severe for steel hardness exceeding HRC 22 (Rockwell C, approximately equivalent to HV 233 Vickers). The gathering network pipeline girth welds, particularly the heat-affected zone (HAZ) immediately adjacent to the weld fusion line, routinely exhibit hardness values in the range HRC 24--28 under as-welded conditions — above the NACE threshold — due to the low heat input, high cooling rate welding practice used in field conditions. These hard zones are the primary initiation sites for SSC and the related mechanism of SOHIC.

Mechanism 3: Stress-oriented hydrogen-induced cracking (SOHIC). SOHIC is a particularly insidious failure mechanism that initiates at internal hydrogen-induced cracks (HIC) in the pipe body or at weld HAZ microstructural heterogeneities (carbide-rich zones, martensite islands, grain boundary segregation zones) and then propagates in a direction perpendicular to the applied hoop stress — that is, directly through the pipe wall. SOHIC failures typically produce no ILI-detectable metal loss until a crack has propagated approximately 50--70% of the way through the wall, at which point conventional MFL tools may detect a stress concentration anomaly but cannot distinguish the cause. All three historical failure events at the field exhibited SOHIC crack morphology in post-failure metallurgical examination — yet all three were classified as no-anomaly by MFL ILI immediately prior to failure, confirming the diagnostic blind spot of conventional inspection for this failure mechanism.

Why conventional models fail. The operator's previous corrosion management approach — steady-state de Waard--Milliams electrochemical model, continuous 2-ethylhexyl phosphate ester inhibitor injection at 40 ppm, 90-day MFL ILI, and quarterly corrosion coupon retrieval — failed to identify the SOHIC risk for several interconnected reasons. The de Waard--Milliams model predicts generalised corrosion rates but contains no physics for hydrogen uptake, diffusion through the steel lattice, or trap-controlled accumulation. MFL ILI detects metal loss (generalised corrosion) but not sub-surface crack indications (SOHIC) until very late stage. Corrosion coupons measure generalised mass loss but not localised crack-driving hydrogen concentration. And the phosphate ester inhibitor has documented performance degradation in the presence of FeS scale — the scale that forms preferentially at pH2S > 0.5 MPa — because the FeS surface competes with and displaces the inhibitor film.

Real-World Basis

This study draws directly from the Kashagan field (North Caspian Operating Company, Kazakhstan), which began limited production on September 11, 2013, and was shut in within two weeks when H2S leaks were detected from the sour gas export pipeline connecting the artificial island facilities to the onshore Bolashak processing facility at Karabatan.

The Kashagan field. Kashagan is located in the northern Caspian Sea, approximately 80 km south-southeast of Atyrau, Kazakhstan. It is one of the largest oil fields discovered since the 1960s, with estimated recoverable reserves of 9--13 billion barrels. The reservoir is a deeply buried, highly fractured carbonate (Carboniferous limestone and dolomite) at approximately 5,000--5,500 m depth, with initial reservoir pressure of approximately 1,050 bar (105 MPa) and temperatures of 100--120°C. The H2S content of the reservoir gas phase is approximately 19%, making it one of the most sour producing fields in the world. At wellhead conditions, the produced gas stream has pH2S in the range of 0.8--1.8 MPa depending on operating pressure.

The pipeline failures. The offshore-to-onshore pipeline system comprises approximately 100 km of subsea pipeline (partially buried in the Caspian seabed) connecting the artificial island facilities (Islands A, B, C, D) to the Bolashak processing facility. The system includes two 30-inch pipelines — one for sour gas export, one for crude oil export — plus smaller lines. Both major pipelines were constructed from carbon steel with internal CRA (corrosion-resistant alloy) cladding.

On September 24, 2013, a gas leak was detected from the ground pipeline section. Production was suspended, resumed, then suspended again on October 9, 2013, after detection of a second leak. NCOC investigation, with metallurgical analysis performed by TWI Cambridge (The Welding Institute), identified the root cause as sulphide stress cracking (SSC) caused by the formation of "local hard zones" (LHZs) in the pipeline body — regions of anomalously high hardness (HRC > 22) produced during the thermo-mechanically controlled processing (TMCP) of the line pipe steel, where small variations in steel plate surface oxide thickness caused extreme local cooling rate variation during the TMCP accelerated cooling step, producing martensitic or bainitic microstructural patches with hardness up to HRC 28--32.

Scale of the failure and replacement. NCOC's investigation concluded that approximately 200 km of pipeline would require replacement. The replacement programme — using inconel-clad (Alloy 625) carbon steel pipe for the sour gas service lines and improved CRA cladding for the crude oil lines — was completed by mid-2016. The estimated direct cost of replacement was USD 3.6 billion. During the 2013--2016 shutdown, Kashagan produced essentially no revenue from what was projected to be 370,000 barrels/day of production; at USD 80/barrel (approximate 2013--2015 average price), the deferred revenue loss amounts to approximately USD 32 billion over approximately 1,000 days, though a more realistic economic loss figure accounting for production ramp-up that would not have been achieved immediately is cited in published consortium financial disclosures as approximately USD 16 billion in total consequence.

Regulatory and institutional findings. The Kazakhstani Ministry of Energy levied a USD 735 million environmental fine on NCOC in March 2014 for the H2S release resulting from the emergency flaring of pipeline contents during the shutdown. The NCOC consortium's technical post-mortem confirmed that H2S partial pressure in service exceeded the design assumptions used in materials qualification, that the NACE MR0175/ISO 15156 qualification testing had been conducted at sub-ambient pH2S conditions, and that the original pipeline manufacturer's TMCP process had not been adequately controlled to prevent LHZ formation.

Material selection lesson. The original pipeline material selection had used 22Cr duplex stainless steel for portions of the system, which the NCOC investigation determined to be marginal at pH2S > 1.2 MPa due to the combined risk of SSC (from H2S) and pitting corrosion (from the Caspian Sea produced water's high chloride content, approximately 180,000 ppm TDS). The replacement material selection — Alloy 825 (UNS N08825) cladding on carbon steel — provides superior SOHIC and SSC resistance at the field's pH2S operating envelope, consistent with the molecular-scale hydrogen permeability comparison across material options in this study.

Simulation Approach

The petrosim platform applies a three-scale simulation chain specifically developed for sour service integrity assessment:

Molecular scale. The sour corrosion module uses reactive molecular dynamics to model the Fe/H₂S/CO₂/H₂O interfacial reaction chemistry — the reactions that generate atomic hydrogen at the pipe wall and drive it into the steel. Key outputs include the atomic hydrogen generation rate at the steel surface from H₂S dissociation as a function of pH2S, temperature, and FeS scale coverage; the hydrogen diffusion coefficient D_H(T) through the iron lattice as a function of temperature and microstructural trap density (grain boundaries, carbide precipitates, dislocation density — parameterised from the operator's weld procedure qualification metallurgical records); and FeS scale phase stability covering formation rate and thermodynamic stability of mackinawite (metastable), troilite (stable), and pyrite under the field's temperature and partial pressure conditions. Thin, porous mackinawite scale acts as a cathodic depolariser (accelerating corrosion), while thick, dense troilite scale provides a partial diffusion barrier; the ratio of scale morphologies — controlled by temperature, pH2S, and pH — determines the net effect on corrosion rate.

Quantum chemistry calculations (newtsim Root) provide adsorption energies for the phosphate ester inhibitor on FeS and bare Fe surfaces. The computed Delta-G_ads for phosphate ester on FeS is -28 kJ/mol, versus -67 kJ/mol on bare Fe — indicating a 2.4x weaker binding constant and 31--41% lower equilibrium surface coverage at the same injection dose. This quantifies the inhibitor performance degradation in the presence of FeS scale and explains why the operator's inhibitor achieves only 44--52% efficiency (measured) vs. the vendor-claimed 65--75% (tested on clean steel).

Mesoscale. The mesoscale model couples a hydrogen diffusion-trap model to a fracture mechanics SOHIC crack growth model. Hydrogen flux from the inner pipe surface (computed from the molecular-scale corrosion rate) diffuses through the steel wall, accumulating at microstructural traps — grain boundaries, carbide precipitates, and dislocation tangles. The local hydrogen concentration at each trap type is compared to the critical concentration H_c for hydrogen embrittlement onset (parameterised from NACE TM0177 slow strain rate test data for X65 steel in H2S environments). When local hydrogen concentration exceeds H_c, a SOHIC crack initiation event is triggered; subsequent crack growth follows fracture mechanics, calibrated from published X65 steel data in H₂S environments at 73--94°C. The rationale for this coupled approach is that it captures the mechanism MFL inline inspection cannot see: sub-surface hydrogen accumulation driving cracks through the wall before any metal loss is detectable.

Field scale. Field-scale outputs aggregate the segment-level corrosion rates and SOHIC probability distributions into a network-wide integrity map covering all 340 km. For each of the 127 ILI inspection segments in the gathering network, the model computes expected metal loss from electrochemical corrosion, SOHIC crack initiation probability, and remaining life distribution (P10/P50/P90). The field-scale model also optimises inhibitor injection across the network's 34 injection points — answering the question of where to spend chemical budget for maximum integrity benefit.

Simulation Caveats

Classification: STRETCH. The sour service integrity module is one of the most computationally demanding in the petrosim suite, coupling reactive molecular dynamics (Fe/H₂S/CO₂/H₂O interfacial chemistry) with quantum chemistry inhibitor adsorption calculations, a hydrogen diffusion-trap model, and a fracture mechanics SOHIC crack growth model. Each stage introduces assumptions that compound through the chain; the 71% positive predictive value demonstrated over 22 months is a strong empirical result, but its limitations should be clearly communicated.

The reactive force field parameterisation was originally developed and validated for binary Fe/H₂O and Fe/H₂S systems. Its application to the simultaneous four-component environment (H₂S, CO₂, H₂O, Cl-) at pH2S up to 1.6 MPa and 94°C represents an extrapolation beyond the original validation envelope. The atomic hydrogen generation rate — the primary input to the hydrogen diffusion model — carries a systematic uncertainty estimated at ±20--30% at the field's extreme pH2S conditions, propagating directly into the SOHIC initiation probability.

The hydrogen diffusion-trap model requires trap density inputs for grain boundaries, carbide precipitates, and dislocation density. These are estimated from the operator's weld procedure qualification metallurgical records, which characterise average HAZ microstructure rather than the specific weld-by-weld variation across 312 girth welds. Welds with atypically high carbide density or martensite island fraction — not captured in the WPQ database — may accumulate hydrogen faster than predicted, contributing to the 2 false negatives in the 22-month audit.

The crack growth constants (C = 2.1 x 10⁻¹² m/cycle, m = 3.4) are calibrated from published X65 fracture mechanics data in H₂S environments, but published scatter in Paris law constants for H₂S-embrittled X65 spans approximately one order of magnitude in C. The time-to-through-wall predictions carry a corresponding factor-of-2 to factor-of-3 uncertainty at P90, meaning predicted remaining life intervals should be used for inspection scheduling priorities rather than hard go/no-go decisions without TOFD confirmation.

The quantum-chemistry-computed adsorption energies on mackinawite FeS surfaces use a simplified stoichiometric FeS slab model. Real pipe-wall FeS scales are phase mixtures (mackinawite, troilite, pyrite) with significant surface area heterogeneity and partial amorphous character. The predicted 31--41% lower surface coverage for phosphate ester on FeS is directionally correct and experimentally corroborated by the measured inhibitor underperformance, but the absolute magnitude of the coverage reduction carries ±10 percentage points uncertainty from the surface model simplification.

Recommended framing: Lead with the empirical validation result — 71% PPV for SOHIC prediction versus 40--55% for empirical correlations — as the primary evidence of model value. Acknowledge the two false positives as expected given the model's conservative parameterisation, and position them as welds under continued monitoring rather than model failures. For materials selection recommendations, note that the molecular-scale hydrogen permeability hierarchy (X65 >> 22Cr duplex >> Alloy 825 >> Inconel 625) is robustly directional even with ±30% uncertainty on absolute values, and is independently supported by published NACE qualification data.

Key Predictions / Results

The following table compares predictions made at deployment (month 0) against outcomes measured over the 22-month audit period:

Parameter	Petrosim prediction (month 0)	Measured outcome (22 months)	Agreement
General corrosion rate — mid-network, 73°C, pH2S 0.8 MPa	0.38–0.54 mm/yr	0.41–0.57 mm/yr (coupon retrieval)	Within 8%
General corrosion rate — trunk lines, 94°C, pH2S 1.6 MPa	0.61–0.82 mm/yr	0.65–0.88 mm/yr	Within 7%
Phosphate ester (40 ppm) inhibitor efficiency	42–55% reduction (predicted, accounting for FeS)	44–52% reduction (measured coupons)	Within 6%
Vendor-claimed inhibitor efficiency (for reference)	65–75% on clean steel	Not applicable in service	Overestimate confirmed
SOHIC crack initiation: welds exceeding H_c threshold at P50 (36 months)	7 of 312 girth welds predicted	5 of 7 confirmed by TOFD at 18 months	71% PPV
SOHIC false negative rate — 3 historical failure locations	All 3 retroactively classified >60% risk	All 3 failed — mechanism confirmed	100% retrospective
Inhibitor uplift: 75 ppm maleic acid copolymer	Projected 61–68% CR reduction	Not yet implemented — forecast	—
Recommended replacement material: Alloy 825	SOHIC-resistant to pH2S 1.6 MPa	Consistent with Kashagan replacement choice	Independently confirmed
22Cr duplex stainless steel at pH2S > 1.2 MPa	Marginal — chloride pitting risk	Confirmed inadequate — Kashagan precedent	Validated
Projected remaining life, revised strategy (P50)	11–14 years	3.8 years historical (baseline for comparison)	3–4x extension predicted

Material SOHIC/SSC risk vs cost — hydrogen diffusivity comparison for 6 material options at pH₂S 1.6 MPa

SOHIC prediction detail. The 7 predicted high-risk girth welds were identified based on three convergent risk factors: weld HAZ Vickers hardness exceeding HV 233 (from the operator's weld procedure qualification records), computed H flux at that wall location exceeding the critical H_c threshold from NACE TM0177 data at the local pH2S, and pipeline operating hoop stress above 40% SMYS (providing the tensile stress field required for SOHIC crack orientation and growth). The 5 confirmed SOHIC indications at TOFD re-inspection represent a 71% positive predictive value — substantially outperforming the 40--55% PPV typically achieved by empirical DNV RP-F112 correlations without microstructural input.

Risk map — gathering network SOHIC classification:

Inhibitor performance and FeS interaction. The DFT finding that phosphate ester adsorption energy on FeS is 59% weaker than on bare Fe provides a first-principles explanation for the observed inhibitor underperformance. At pH2S > 0.5 MPa — which applies throughout the gathering network — FeS scale (primarily mackinawite at these temperatures) forms rapidly and covers a significant fraction of the pipe wall surface. The lower Delta-G_ads for the phosphate ester on FeS means the inhibitor is partially displaced from FeS-covered regions, effectively leaving those regions uninhibited at the dosage applied. The recommended switch to a maleic acid copolymer inhibitor — which the DFT model predicts has a Delta-G_ads on FeS of -54 kJ/mol (nearly equivalent to its -71 kJ/mol adsorption on bare Fe) — addresses this mechanism, with projected efficiency of 61--68% at 75 ppm dosing.

Materials selection quantitative comparison:

Material	H permeability at pH2S 1.6 MPa, 90°C	SSC risk	Chloride pitting risk	Cost index (API 5L X65 = 1.0)
API 5L X65 (current, HAZ HV 260)	High — D_H = 3.8 × 10⁻⁶ cm²/s	High — SSC confirmed	Low	1.0
API 5L X65 (HAZ HV ≤ 220, controlled WPS)	Moderate — D_H = 2.1 × 10⁻⁶ cm²/s	Moderate — below NACE threshold	Low	1.15
22Cr duplex stainless steel (UNS S32205)	Low — D_H = 0.4 × 10⁻⁶ cm²/s	Low at pH2S < 1.2 MPa	Moderate at Cl > 150,000 ppm	4.8
Alloy 825 (UNS N08825) solid	Very low — D_H = 0.08 × 10⁻⁶ cm²/s	Negligible	Very low	12.4
Alloy 825 clad on X65	Very low (clad controls permeation)	Negligible	Very low	3.8
Inconel 625 (UNS N06625) clad on X65	Negligible	Negligible	Negligible (benchmark CRA)	5.2

The recommended solution for replacement sections is Alloy 825 CRA clad on API 5L X65 substrate — providing the required SOHIC resistance at pH2S up to 1.6 MPa while limiting material cost to approximately 3.8x the baseline carbon steel cost. This is consistent with the Kashagan replacement choice of inconel-clad pipe for the most critical sections.

Remaining life projection — three management scenarios:

SOHIC risk reduction vs incremental capital cost — three management scenarios for priority girth weld network

Comparison Methodology

The 22-month post-deployment audit applies a five-layer validation framework. The primary validation is the higher-fidelity molecular and mesoscale models benchmarked against the field-scale integrity predictions. Operational measurements and published data provide secondary confirmation.

The first layer is corrosion coupon mass loss. Quarterly coupon retrieval at 12 network monitoring stations provides direct measurement of generalised corrosion rate. Predictions at each station location (specific to local pH2S, temperature, flow velocity, inhibitor concentration) are compared to measured mass-loss rates. Agreement is within 8% across all 12 stations over the 22-month period.

The second layer is ILI metal loss comparison. 90-day MFL ILI results over the audit period are compared to the predicted metal loss accumulation at ILI feature locations, validating the electrochemical corrosion submodel. Predicted metal loss rates agree with ILI delta measurements within ±12% at ILI-detectable features — noting that the most dangerous failure mechanism (SOHIC) is not detected by MFL ILI.

The third layer is TOFD crack detection vs. SOHIC prediction. TOFD ultrasonic inspection results at the 7 predicted SOHIC hotspots provide direct validation of the crack initiation model. The 71% positive predictive value (5 of 7 predicted confirmed by TOFD at 18 months) is benchmarked against DNV RP-F112 empirical correlations, which typically achieve 40--55% PPV without microstructural input, and against industry expectation for SOHIC prediction. The 2 false positives (predicted but not detected by TOFD at 18 months) are under continued monitoring as the model projects they may initiate in the 18--36 month window — consistent with the P10 prediction at those weld locations.

The fourth layer is the Kashagan published failure analysis. Root cause analysis data from NCOC's published post-incident reports are used to validate the molecular-scale model's prediction of hydrogen generation rates and FeS scale phase stability at Kashagan-equivalent conditions. The Kashagan TWI metallurgical investigation finding of SSC initiation at "local hard zones" (LHZs, HRC > 22) is entirely consistent with the SOHIC initiation criterion targeting HAZ locations exceeding HV 233.

The fifth layer is NACE MR0175 qualification test data. The hydrogen permeability predictions for Alloy 825 and X65 steel at the field's pH2S conditions are compared against published NACE TM0177 and ISO 15156 qualification test datasets. The molecular-scale hydrogen diffusion coefficient for X65 (D_H = 3.8 x 10⁻⁶ cm²/s at pH2S 1.6 MPa, 90°C) is consistent with the published experimental range of 2.9--4.8 x 10⁻⁶ cm²/s from NACE TM0177 testing at comparable conditions, confirming the force field parameterisation.

Deliverables

22-month post-deployment audit report with quantitative comparison of predictions vs. measured data across all 12 corrosion monitoring stations, 127 ILI segments, and 7 SOHIC prediction hotspots, with a formal statistical analysis of model performance (PPV, false negative rate, bias, and precision)
Updated field-wide integrity map with SOHIC risk classification for all 312 girth welds in the priority network segment, formatted for the operator's Integrity Management Plan (IMP) submission to the Kazakhstani Ministry of Energy
Materials selection guidance: quantitative SOHIC risk comparison for API 5L X65 (baseline), X65 with controlled HAZ hardness (WPS upgrade), 22Cr duplex stainless steel, Alloy 825 clad on X65, and Inconel 625 clad on X65, at the field's pH2S/pCO2 operating envelope — including cost index and remaining life projection for each option
Inhibitor optimisation report: DFT-derived dose-response data for 4 candidate formulations (phosphate ester, maleic acid copolymer, imidazoline, and phosphono-carboxylic acid copolymer) at field conditions, with recommendation and projected performance; includes FeS compatibility assessment for each formulation
Revised ILI and TOFD inspection schedule, risk-ranked by segment SOHIC probability, with recommended inspection intervals for each of the 4 pipeline risk classes (critical/elevated/monitor/low risk)
Remaining life distribution report (P10/P50/P90) for all network segments under 3 management scenarios (current, recommended, accelerated replacement), formatted for use in RBI (risk-based inspection) software
Integration specification for continuous monitoring: automated TOFD data ingestion and SOHIC probability update protocol, including alert thresholds and recommended action decision tree

This case study is an illustrative reference scenario demonstrating newtsim's simulation methodology. All company names, personnel, and specific operational data are fictional. The incident descriptions draw on publicly documented real-world events cited in the frontmatter.