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A Historical Review of Earth Model Building

By Dr. Ian F. Jones1, Dr. John Brittan1, Johnny Chigbo1, Dr. Gloria Awobasivwe2, Christopher Osolo2 and Paula Ukerun2 1: ION Geophysical;  2: Bulwark Services Nigeria

Introduction

In this review article, we consider the development of subsurface parameter estimation for use in building subsurface images for geological interpretation and reservoir evaluation using seismic migration procedures. We outline the progressive evolution form a purely linear approach wherein no reference was made for consistency between the various steps in the procedures, to the emerging approach of a closed-loop iterative workflow wherein each step is checked for internal consistency, and the parameter fields updated until all steps in the procedures are mutually consistent (Brittan and Jones, 2019).

In seismic data processing we aim to: separate ‘signal’ from ‘noise’; build an anisotropic velocity model; migrate the data, producing ‘true amplitude’ angle classes that are then used for elastic parameter estimation for reservoir characterisation. The parameter estimation techniques we have are limited in their resolution, and this restricts the accuracy and precision of the images we can produce. In general, with conventional tomographic velocity update we are limited by the ray-theory ‘scattering limit’ to a resolution of perhaps 5x the available sound-wavelength. Hence we are modest in what parameters we try to estimate tomographically, at best obtaining a smooth anisotropic velocity field suitable for migration, with features with lateral scales of about 500m.  Many excellent results have been obtained with ray methods, and developments (such as well and structural constraints) continue to improve them. Conversely, parameter estimation using ‘full waveform inversion’ (FWI) can perhaps deliver resolution of about half the available sound-wavelength, so theoretically perhaps ten-times the resolution of ray methods. FWI primarily uses the transmitted (refracted) wavefield rather than the reflected wavefield, and typically ignores density contrast, attenuation (Q), etc., (e.g. Virieux and Operto, 2009; Jones 2010, 2018).

For the majority of geological environments, building a model with FWI will not result in an image that is radically different than that obtained using tomography. The exception to this observation would be in shallow water with small-scale anomalies (e.g. over-pressured gas), or for deep subsalt reservoirs (and then only if we have low frequencies and long offsets). Along with better well-ties and potentially better images, the additional promise of FWI is in delivering high resolution interpretable attribute fields directly and quickly

Here, we’ll assess the development of the data processing procedures involved in obtaining subsurface parameter fields for use in migration, and consider how these methods have developed over the past thirty-odd years, and what their future development direction might be.

Figure 1. The ‘S-curve’ development profile for any technology development, in the context of tomography and FWI.

Historical Background

In the life-cycle of any technological development, there is a slow development phase when our initial understanding is poor but growing, followed by rapid development once the fundamentals of the process are fully comprehended, and finally further development levels-out as the method is then fully exploited (Figure 1).

Historically, seismic data processing workflows were purely linear. Field data were ‘processed’, a rudimentary velocity model was estimated from stacking velocity picking, using map migration to depth-locate picked time-horizons, and migration was performed. These tasks happened just once.

From about 1995 onwards, with the introduction of ray-based tomography, the model building element changed to become doubly iterative, in that repeated ray-trace modelling was utilized within an inversion scheme, so as to converge on a model that produced flat common-reflection-point (CRP) gathers, after several iterations of migration. As it is comparing data after migration, this technique is an ‘image domain’ inversion scheme, and hence it is not looking for consistency with the raw input data.

Since about 2005, FWI has been gradually introduced, modifying the tomographic solution by using wavefield-extrapolation modelling so as to iteratively match forward modelled synthetic data with measured field data. Hence, this methodology does indeed ‘refer back’ to the raw input data, but as the inversion is performed in the ‘data domain’, and still has limiting assumptions, the resulting model is not guaranteed to produce ‘flat gathers’ in the ensuant migration

What are the respective parameter resolutions available from these two methods? The resolution of ray-tomography is limited to cell-sizes of perhaps 100*100*25m, as on scale lengths smaller than this, the ray theory approximation fails. Conversely, waveform methods use a cell size of potentially less than 15*15*15m … hence we can expect much better lateral resolution in the parameters in the near surface, and overall better resolution in the deep section.

However, none of these approaches and subsequent migrations attempted to compensate for the underlying ‘bad physics’ or ‘bad data’ that we were employing. For example, using a one-way acoustic wave equation, and with field data that are poorly and/or irregularly sampled, and containing remnant multiples and possibly mode-converted energy. Hence, the least-squares migration technique was introduced to attempt to compensate for some of these issues, in that another iterative inversion loop is introduced so as to form an image (and/or gathers) consistent with the input field data (Schuster, 1997). However, this does not simultaneously try to modify the subsurface model, and still assumes that data are multiple-free.

Figure 2. Flow chart representation of: a) the historical ‘linear’ approach to imaging, b) image-domain ray-based tomography, c) data-domain FWI, d) least-squares update (which can be applied in either the image or the data domain). (Adapted from Vershuur and Berkhout, 2015).

Figure 2 outlines the above methods in a series of flow-charts, and indicates a gradual transition from incremental modification of existing ‘open loop’ solutions, to more transformational and fully ‘closed loop’ solutions. A ‘closed loop’ solution would use a two-way elastic description of sound propagation, iteratively referring back to the field data, iteratively updating the model, and at each step iteratively constraining image gathers to be flat. And ultimately, evolving into inversion for high frequency elastic Earth parameter models, having made use of the full wavefield (including multiples and elastic mode conversion effects).

What are the main differences between incremental and transformational developments? Conventional methods, and their associated incremental developments, primarily are non-iterative over the entire workflow: some bits may be iterative (such as tomographic model update, or LS image enhancement), but the overall flow, from input data to final elastic parameters, is dealt with as a more or less a linear single-pass approach. Conversely, the transformational routes offer adaptive iteration over a larger part of the entire workflow, with the possibility of exploiting the full wavefield (multiples, conversions, etc.).

What is the motivation for moving beyond current ‘best-practice’? Ultimately, resolving a number of reservoir attributes to the extent that they can directly influence drilling decisions and further reduce risk. And, to exploit the full wavefield to the maximum extent possible (exploit multiples, elastic effects, etc., to make full use of all energy in the recorded data).

At present, the limiting assumptions we make in waveform inversion limit what we can achieve: we can currently forward model with a priori parameters for: anisotropic Vp, density, attenuation, (and perhaps Vs), but generally we invert only for P-wave anisotropic velocity. However, if we can push the frequency range of the inversion (which is very expensive), and invert for: anisotropic Vp, density, attenuation, (and perhaps Vs). Then we can directly output the desired elastic parameter volumes, rather than resorting to the intermediate step of migrated gathers which would then be used to perform very approximate reservoir parameter estimation.

What technologies are required to fulfil these ambitions? It is well known that low frequencies are required to facilitate the convergence of FWI (typically with less than perhaps 1.5 Hz). This requirement has led to a recent surge in development of low frequency (or enhanced frequency) sources (Brenders et al., 2018; Brittan et al., 2019). Long offsets are also of benefit, hence ocean bottom recordings are beneficial (Brittan et al. 2013). And, elastic modelling and associated parameter estimation will also be beneficial, and perhaps crucial for land data, were elastic effects severely affect sound propagation.

The Road Ahead

Currently, migration algorithms assume that all multiple energy (reverberation within layers) has been removed from the input data. Removing this restriction would enable us to make use of virtually

all the recorded energy in the field data. One method to achieve this goal is referred to as ‘full wavefield migration’ (FWM), outlined in Figure 3 (Verschuur and Berkhout, 2015). Adding a simultaneous update of the velocity field to this work-flow produces the ‘joint migration inversion’ scheme (JMI – Figure 3b). But ultimately, the objective would be to input the field data (with all its various arrival events) into an inversion scheme, and then directly output all requisite elastic parameters at a resolution sufficient to facilitate direct interpretation (Figure 3d): this was the goal originally envisaged by Tarantola (1984). However, this latter route is still beyond the reach of application as a routine process, but has been demonstrated in a few examples (e.g. Routh et al., 2018).

As an intermediate solution, we can employ the velocity field from FWI to better constrain conventional post-migration impedance inversion: this approach was first suggested by Cobo et al. (2019), and is outlined as a flow-chart in Figure 3c. Below we show an example of their approach (Jones et al., 2018), comparing a impedance inversion using a ‘conventional-constraint’ employing well-logs and interpreted horizons, with an FWI-only-

Figure 3. Flow chart representation of: a) full wavefield migration, b) joint migration inversion, c) impedance inversion constrained using FWI, d) full elastic FWI for direct multi-parameter estimation. (Adapted from Vershuur and Berkhout, 2015).

constraint, that uses no wells nor any picked horizons. Figure 4 shows results from Ophir’s Fortuna field (offshore Equatorial Guinea). This compares the result of a blind-test at the location of well-log which was not used to build the conventional constraints. Here, we are away from the location where the conventional result’s constraints were built, and as seen in the well-log comparison, use of the FWI constraint has resulted in a better match than the more conventional approach.

Conclusions

The evolution of FWI as a tool to improve velocity models for migration, and the move towards using such models for more direct reservoir characterization, has transformed and continues to transform the application of closed-loop’ transformational processes within exploration and production imaging projects. There remain, however, some key challenges to further successful exploitation of such methodologies: namely developing a better understanding of elastic wave propagation effects, and in obtaining the computer power to implement numerical schemes based on such an enhanced understanding.

Figure 4. In the blind-test, the FWI constrained results match the well more closely than the conventional result (courtesy of Ophir Energy and Jones et al., 2018).

Acknowledgements

The authors would like to thank the ION and Bulwark teams that have contributed to this work:  Tristram Burley, Carlos Calderón, Shihong Chi, Yannick Cobo, Paul Farmer, Juergen Fruehn, Stuart Greenwood, Claudia Hagen, Gary Martin, Ross O’Driscoll, Jeet Singh, Chao Wang and David Yingst. 

References

Brenders, A., Dellinger, J., Kanu, C., Li, Q., Michell, S., [2018].  The Wolfspar© field trial: Results from a low-frequency survey designed for FWI.  Expanded abstracts for the 88th SEG meeting, FWI 2.1

Brittan, J., Bai, J., Delome, H., Wang, C. and Yingst, D., [2013]. Full waveform inversion – the state of the art. First Break, 31, 75-81.

Brittan, J., and Jones, I.F, [2019]. FWI evolution – from a monolith to a toolkit, The Leading Edge, 38, no.3, 179-184.

Brittan, J., Farmer, P., Bernitsas, N., and Dudley, T., [2019]. Enhanced low frequency signal to noise characteristics of an airgun technology based source. Workshop 9, 89th SEG meeting,

Cobo, Y., Calderón-Macías, C. and Chi, S., [2018].  Improving model resolution with FWI for imaging and interpretation in a Gulf of Mexico data set. Expanded abstracts for the 88th SEG meeting, FWI 2.2

Jones, I.F., [2018]. Velocities, Imaging, and Waveform Inversion (The evolution of characterizing the Earth’s subsurface), EET 13, EAGE, 234 pages.

Jones, I.F., Singh, J., Greenwood, S., Chigbo, J., Cox, P. and Hawke, C., [2018].  High-resolution impedance estimation using refraction and reflection FWI constraints: the Fortuna region, offshore Equatorial Guinea. First Break, 36, November, 39-44.

Jones, I.F., [2010]. An introduction to velocity model building, EAGE, ISBN 978-90-73781-84-9, 296 pages.

Routh , P., Neelamani , R., Lu , R., Lazaratos , S., Braaksma , H., Hughes , S., Saltzer, R.,  Stewart , J., Naidu , K., Averill , H., Gottumukkula ,V.,  Homonko , P., Reilly , J., and Leslie, D., [2017]. Impact of high-resolution FWI in the Western Black Sea: Revealing overburden and reservoir complexity. The Leading Edge, 36(1), 60–66.

Schuster, G., [1997]. Acquisition footprint removal by least square migration: 1997 Annual UTAM Report, 73-99.

Tarantola, A., [1984]. Inversion of Seismic Reflection Data in the Acoustic Approximation, Geophysics, 49, 1259-1266.

Verschuur, D.J. and Berkhout, A.J., [2015]. From removing to using multiples in closed-loop imaging. The Leading Edge, 34 (7), 744–759.

Virieux, J. and Operto, S., [2009]. An overview of full-waveform inversion in exploration geophysics.  Geophysics, 74, WCC1-WCC26.

 


Most of Ghana’s Gas Is Stranded

By Foluso Ogunsan

More than half of natural gas produced in Ghana in 2019 has had to be reinjected for lack of availability of off takers, the country’s annual petroleum industry report has indicated.

“In spite of the fact that Ghana National Gas Company(GNGC), managed to bring on stream new off takers during the reporting period, namely Amandi Energy at Aboadze, Karpowership at Sekondi, Genser, at Tarkwa, and shipment of gas from Takoradi to Tema, through the West Africa Gas Pipeline, a substantial amount of the country’s gas remains stranded”, the Public Interest Accountability Committee (PIAC) notes in its 2019 annual report, released recently.

More than half (56.87%) of total gas produced from Jubilee, TEN, and SGN had to be reinjected during the period.

The committee says that “2018 price of lean gas was slashed by 31.23% in 2019. The reduction means cheaper fuel for thermal power generation”.

The PIAC is Ghana’s equivalent of an Extractive Industry Transparency Initiative (EITI).

The report says that Ghana National Petroleum Corporation (GNPC), supplied $334,636,806.22 (~$334.6Million) worth of raw gas to GNGC, but no payment was received, largely on account of the inability of the Volta River Authority, the state power utility, to pay GNGC for the lean gas supplied.

“Added to the outstanding balance of $333,481,539.82 (~$333Million), this brings the total indebtedness of GNGC to GNPC in respect of lean gas supplies to $668,118,346.04 (~$668Million).

The GNGC is on course to become Africa’s most indebted state hydrocarbon company.

 

 


Sasol Closer to Selling Stakes in EGTL, Moza Gas Pipeline

By Toyin Akinosho

South African synfuels giant Sasol, says it has signed an agreement with Chevron Corporation for the sale of its indirect beneficial interest in the Escravos Gas to Liquids (EGTL) plant, in Nigeria.

The company has also inched close to finalizing the sale of its equity in the Republic of Mozambique Pipeline Investment Company (Rompco) and the Central Termica de Ressano Garcia gas-fired power plant, also in Mozambique.

EGTL commenced beneficial operations in June 2014, 15 years after the idea first came on the drawing board. Its original cost started out at $1.9Billion, when Final Investment Decision was taken in 2005. The cost rose to $5.9Bllion in 2009 but continued to escalate, raising government and partner concerns.  The plant has an initial capacity of 34,000 barrels per day.

Chevron Corp signed global JV with Sasol Ltd as well as the global JV supplementary agreement that specifically related to Nigeria. In the beginning it was 50:50 risk sharing agreement between the two companies. The agreement with Sasol is offshore and managed as such. In Nigeria, state owned firm NNPC took 25% and Chevron Nigeria had 75%. As costs escalated and the project was delayed, Sasol drastically reduced its stake.

 In its release, Sasol did not disclose how much it expected to make for the EGTL disposal, but it did say that the transaction had an agreed economic effective date of September 1, 2019.

The Rompco pipeline, an 865km facility which transports around 500Million standard cubic feet a day of gas from Sasol’s Pande and Temane gasfields, in southern Mozambique, to South Africa, is a more strategic asset to Sasol.

The other shareholders in the pipeline include the Mozambican state hydrocarbon company Companhia Mocambiçana de Gasoduto (25%) and the South African Gas Development Company (25%), also known as iGas, a subsidiary of South Africa’s Central Energy Fund (CEF).

Sasol is aiming to realise between $2- and $5-Billion in proceeds from the disposals, initiated to help reduce its $10Billion debt burden by $6-billion by the end of its 2021 financial year.


TOTAL Will Now Drill Follow Ups in South Africa, From September 2020

TOTAL will return to drill in the rough waters offshore South Africa’s Cape Agulhas in September.

The French major will be commencing a multi-well drilling programme, beginning with the spud of the Luiperd Prospect, in the first follow -up to the Brulpadda oil and gas discovery it encountered in February 2019.

Luiperd-1, reputed to be the largest prospect in the Paddavissie Fairway (on which the Brulpadda itself is hosted), will be the first to be drilled by the semisubmersible rig Deepsea Stavanger, operated by Odfjell Drilling.  Two other wells are expected to follow in short order.

That the rig is currently mobilizing from Norway to South Africa, indicates the end of the idle period in the agreement between TOTAL South Africa and Odfjell Drilling. The programme was to have commenced in first quarter 2020, but restrictions effected by COVID-19 complications compelled the two parties to agree  that “Deepsea Stavanger will remain idle in Norway for a period prior to the mobilisation of the rig” and that “Odfjell Drilling will be compensated by TOTAL during this idle time”. The agreement also indicated that “once the idle period is complete, the rig will mobilise to South Africa to commence its charter as planned”.

Africa Energy, a minority partner in the licence holding and operations, declares its excitement “to begin the next phase of exploration drilling on Block 11B/12B offshore South Africa. in order to spud well by September”. The Canadian minnow explains that the prospect, Luiperd ’has been de-risked by the nearby Brulpadda discovery and subsequent 3D seismic work.”

Block 11B/12B is located in the Outeniqua Basin 175 kilometres off the southern coast of South Africa. The block covers an area of approximately 19,000 square kilometers with water depths ranging from 200 to 1,800 meters. The Paddavissie Fairway in the southwest corner of the block includes several large submarine fan prospects.

TOTAL is operator with a 45% participating interest in Block 11B/12B, while Qatar Petroleum and Canada Natural Resources have 25% and 20% participating interests, respectively.

 


ENI Finds New Gas in Egypt’s ‘Great Nooros Area’

Italian explorer ENI says it discovered a single 152 meters thick gas column in the first exploration well it drilled in the North El Hammad license, offshore Egypt’s Nile Delta.

Bashrush, as the prospect is called, is located in 22 metres of water depth, 11 km from the coast and 12 km North-West from the Nooros field and about 1 km west of the Baltim South West field, both already in production.

The gas molecules are stored in sandstones of Messinian age in the Abu Madi formation.

They have excellent petrophysical properties, ENI claims. “The well will be tested for production”, the company says.

“The discovery of Bashrush demonstrates the significant gas and condensate potential of the Messinian formations in this sector of the Egyptian Offshore shallow waters. The discovery of Bashrush further extends to the west the gas potential of the Abu Madi formation reservoirs discovered and produced from the so-called “Great Nooros Area”, the Italian giant explains.

ENI, together with its partners BP and TOTAL, in coordination with the Egyptian Petroleum Sector, will begin screening the development options of this new discovery, with the aim of “fast tracking” production through synergies with the area’s existing infrastructures.

In parallel with the development activities associated with this new discovery, ENI will continue to explore the “Great Nooros Area” with the drilling, this year, of another exploration well called Nidoco NW-1 DIR, located in the Abu Madi West concession.

ENI, through its affiliate IEOC, is 37.5%, equity holder and operator of the North El Hammad concession, in participation with the Egyptian Natural Gas Holding Company (EGAS). BP holds 37.5%, and TOTAL holds  25% of the Contractor interest.

 

 


Cameroon’s Gas to Power Market in Distress

By Sully Manope

The Cameroonian electricity company ENEO (Energy of Cameroon), has announced a 32.6% drop in the production of thermal power stations in the country in the first quarter of 2020.

The reduction (compared with production during the same period in 2019), was due to rationing carried out “at some power stations because of a fuel shortage caused by enormous cash constraints.

ENEO has been unable to pay companies that supply gas to its generators (including Victoria Oil &Gas) as well as companies that generate power from natural gas (Globeleq, Aggreko).

Altaaqa, which supplied the generator ENEO used to convert gas to electricity at Logbagba, in Douala City, suspended operations at ENEO’s Logbaba site in September 2019.

Production capacities at Aggreko operated generating plants at Maroua and Bertoua decreased by almost 60% during the period under review, ENEO reports. Generation from Globeleq operated Kribi and Dibamba gas-fired plants also fell drastically.

This drop in thermal energy production, was, very slightly, offset by increased hydropower production, which had an uptick of 3%.

Overall, the Song Loulou and Edéa hydroelectric plants, both on the Sanaga River, provided 65% of Cameroon’s energy supply over the period.

 


Attar, Algeria’s New Energy Minister, Is back to Familiar Haunts

The Algerian geologist, Abdelmadjid Attar, former CEO of Sonatrach, is his country’s new Minister of Energy.

He takes over from Mohamed Arkab, who has been posted to the less flambouyant Ministry of Mining.

The appointments were part of President Abdelmadjid Tebboune’s partial reshuffle within the government.

Attar was Chief Executive of Sonatrach, Africa’s largest state hydrocarbon company, between 1997 and 1999.

He reached the position after moving up the ranks, taking jobs with increasing responsibilities, including that of director of the exploration division.

Aged 74, Attar obtained the diploma of geological engineering in exploration and attended several trainings in economics and management. He is also the author of several specialized publications.

Mr. Attar is a widely sought-after hydrocarbons consultant in North Africa. He has expressed a keen interest in drawing International Oil Companies back to invest massively in the country.

 


Algeria Extends LNG Supply Agreement to France

TOTAL and Sonatrach have signed an agreement that extends Algerian LNG supply into France by three years.

Algerian state hydrocarbon company Sonatrach will deliver up to 2MillionTonnnes per year of LNG to the LNG terminal at Fos Cavaou, on the entry port to the Mediterranean.

Fos Cavaou is a key gateway to the French and European markets.

The agreement also includes the sub-charter of an LNG tanker from TOTAL by Sonatrach.

Algeria’s initial agreement to supply LNG to France was signed in 2004.

 


FAR Signs New JOAs, But Struggles for Partner to Fund the Next Gambian Well

Australian minnow, FAR, has reported “efforts to find an additional partner for the drilling of the next well in The Gambia”.

FAR is still smarting from the dismal results of the Samo-1 well, drilled in offshore Block A 2 in late 2018. The first exploratory well to be drilled in the Northwest African country in  40 years, Samo-1 was a dry hole.

The company signed new Joint Operating Agreements (JOA’s) in respect of the A2 and A5 Blocks, with the Malaysian state hydrocarbon company f Petroliam Nasional Berhad, PETRONAS).

This follows the granting of new Licences for those Blocks by The Government of The Gambia effective October 1 2019, after which FAR and PETRONAS took the opportunity to update the terms of the existing JOA’s by entering into new JOA’s with effect from 1 October 2019.

FAR remains as Operator under the new JOA’s which better reflect the terms of the new Licences.

FAR says it has “run numerous data room presentations for interested parties” and it is “working to conclude a farm-out before the restart of the drilling operations”.


Gasoline Prices Rise in Ghana, Kenya

Gasoline prices have risen in Kenya by Kenyan Shilling (Sh)5.77 higher per litre, while diesel and kerosene prices dropped by Sh3.80 and Sh17.31 respectively in changes announced by the Energy and Petroleum Regulatory Authority (EPRA) a week ago.

A litre of petrol will cost Sh89.10 per litre in Nairobi, the capital city, an increase from the current Sh83.33 while that of diesel will be sold at Sh74.57. Kerosene will retail at Sh62.46 per litre in the city.

“The changes in this month’s prices are as a result of the average landed cost of super petrol increasing by 31.54% from $188.7 per cubic metre in April to $248.21 per cubic metre in May 2020, diesel increasing 5.58% from $242.13 per cubic metre to $228.62 and kerosene decreasing by 51.84% from $262.44 per cubic metre to $126.39 per cubic metre,” says Pavel Oimeke, EPRA Director General, in a statement.

In Ghana, over the weekend of June 19-21, Shell and Goil, two of the country’s largest Oil Marketers, increased their prices by 4% percent, in addition to the 8% bringing the total increase to about 12% within a week.
But the Executive Director of Ghana’s  Institute of Energy Security (IES), Paa Kwasi Anamua Sakyi, says
other Oil Marketers were unlikely to increase their prices to match Goil and Shell at the pump, r due to competition for market share.

The combined Increase in the depreciation of the local currency Ghana Cedi against the US dollar, the world’s major trading currency, added to the rise in prices of crude oil in the international market, have put pressure on the pump prices in Ghana, the IES says.

Local Kenyan media explain that the recovery on the international crude oil market, “now reverses three months of a steep drop in prices that saw the product sell Sh18 per litre cheaper in April 2020.

They also attribute the marginal drop in diesel prices to “lower demand as summer catches on and the need for heating falls in Europe and America while kerosene, which falls in the same class with Jet A1, lost demand due to the grounding of air travel.

The Energy and Petroleum Regulatory Authority said the changes in the pump prices came as a result of shifts in landed costs of the three products, which decreased for diesel and kerosene and rose for petrol.

The Kenyan government in September introduced a Sh18 per litre adulteration levy on kerosene to discourage its use as an adulterant by a fuel cartel who targeted the wide price margin between kerosene and diesel to make millions.

 

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