The Governing Council of the Nigerian Content Development and Monitoring Board (NCDMB) has approved the expansion of the Nigerian Content Intervention Fund from $200Million to $350Million.
The enlargement of the Fund by $150Million was part of the decisions taken at the recent NCDMB Governing Council meeting, which held virtually on June 16, 2020. The meeting was chaired by Timipre Sylva, the country’s Minister of State for Petroleum Resources and Chairman of the Council.
The Council approved that $100Million from the additional funds would be deployed to boost the five existing loan products of the NCI Fund, which include manufacturing, asset acquisition, contract financing, loan refinancing and community contractor financing.
The Council also approved that $20Million and $30Million respectively should be deployed to two newly developed loan product types – the Intervention Fund for Women in Oil & Gas and PETAN Products, which include Working Capital loans and Capacity Building loans for PETAN member companies.
PETAN is Petroleum Technology Association of Nigeria, a body of Nigerian owned oil service engineering contracting firms.
The NCI Fund was instituted in 2017 as a $200Million Fund managed by the Bank of Industry (BoI), engaged to facilitate on-lending to qualified stakeholders in the Nigerian Oil and Gas industry on five loan product types. The NCI Fund is a portion of the Nigerian Content Development Fund (NCDF), aggregated from the one percent deduction from the value of contracts executed in the upstream sector of the oil and gas industry. About 94 percent of the NCI Funds has been disbursed to 27 beneficiaries as at May 2020. NCDMB has received new applications from 100 companies for nearly triple the size of the original fund.
Guidelines for the NCI Fund provide that beneficiaries of the Manufacturing Loan and Asset acquisition Loan can access a maximum of $10Million respectively. Beneficiaries of Contract finance Loan can access $5Million while beneficiaries of the Loan Re-financing package can access $10Million, with beneficiaries of the Community Contractor Finance Scheme limited to ₦20Million.
The maximum tenure for all loan types is 5 years and applicants cannot have two different loans running simultaneously.
At the onset of the Fund, the applicable interest rate for the various loan types was pegged at eight (8) percent, except the Community Contractor Finance Scheme, which was five (5) percent.
However in April 2020 as part of NCDMB’s response to mitigate economic impact of the coronavirus pandemic, the Governing Council approved reduction of the interest rate from eight (8) to six (6) percent per annum for all four of the loan products. The Board also extended the moratorium for all loan products.
By Dr. Ian F. Jones1, Dr. John Brittan1, Johnny Chigbo1, Dr. Gloria Awobasivwe2, Christopher Osolo2 and Paula Ukerun21: ION Geophysical; 2: Bulwark Services Nigeria
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.
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.
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).
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.
Brittan, J., Bai, J., Delome, H., Wang, C. and Yingst, D., . Full waveform inversion – the state of the art. First Break, 31, 75-81.
Brittan, J., and Jones, I.F, . 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., . 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., . 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., . 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., . 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., . 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., . Impact of high-resolution FWI in the Western Black Sea: Revealing overburden and reservoir complexity. The Leading Edge, 36(1), 60–66.
Schuster, G., . Acquisition footprint removal by least square migration: 1997 Annual UTAM Report, 73-99.
Tarantola, A., . Inversion of Seismic Reflection Data in the Acoustic Approximation, Geophysics, 49, 1259-1266.
Verschuur, D.J. and Berkhout, A.J., . From removing to using multiples in closed-loop imaging. The Leading Edge, 34 (7), 744–759.
Virieux, J. and Operto, S., . An overview of full-waveform inversion in exploration geophysics. Geophysics, 74, WCC1-WCC26.
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.
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 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.
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.
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.
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”.