WO2012146893A2 - Oil & gas exploration and production - Google Patents

Abstract

The invention provides a method and means in oil and gas exploration and production for a depth-based tabulation of sediment rock properties, compiled in one generic oil & gas basin setting, structured to enable conversion of seismic, from basins of any structural or sedimentological history, into properties quantifying seal, reservoir and carrier beds, when keyed, per seismic trace sample, with local current burial depth and the depth equivalent adjustment required to quantify compaction/ digenesis differences between the generic model and local model. Post stack seismic data may be processed to include quantification of key sequence boundaries as a by product of quantifying specific attributes, shapes, seismic stratigraphic detail and velocity distributions, and their spatial rates of change, calibrated by an initial geologic model.

Description

OIL & GAS EXPLORATION AND PRODUCTION

Field of the Invention

This invention relates to oil and gas exploration and production.

The invention is more specifically concerned with the work to be performed to prepare the following, as normalised geophysical and geological and petrophysical (G&G) processing of seismic for oil & gas exploration & production.

Part 1 of this specification concerns the preparation of a 'Normal' model for normalised G&G processing.

Means are described to prepare a generic normal depth based model (geophysics/ geology/ petrophysics) of one geological setting, scalable for use in other settings by means of depth equivalent differences in burial changes.

Part 2 concerns the preparation of 2D & 3D seismic, for normalised conversion of seismic data into geology and petrophysical information.

BACKGROUND TO THE INVENTION

Concerning Exploration and Production of oil fields over 30 million barrels (mb) , E&P's big problem is that geoscience asset team interpretation of lithology & poro-perms (holes in rocks & connectivity) are risky, wasting on average some 50% of exploration & 20% of production cost. So, for 20 years, E&P had found lOBillion barrels Bb p. a., and produced 30.

Figure G5 summarises what seems retrospectively obvious about the benefits of the present invention to double knowledge of poro-perms from seismic data. This is required because now, generation of poro-perm information is still mostly reliant on well data, interpolated to rather than generated from seismic data. That oil fields invariably produce different quantities and over different times than was forecast before production, suggests that the initial geo-poro-perm models were incompletely proper. In exploration, rarely is well data available to define behaviour of all lithologies at all depths.

Current oil & gas E&P geoscience asset teams do not have the methods or means to sensibly quantify rock porosity and permeability at the resolution of seismic (some 10m3) in projects averaging some 500km3, for two reasons. Firstly, good seismic attribute and shape material cannot be yet processed into good material quantifying poro-perms, because depositional lithofacies and burial changes cannot yet be sensibly quantified. (Today's prior art works using local well data, where the assumption is that the local well -based geological model is valid for local geo/ rock physics modelling) . Secondly, per project, even if means existed to do this in a few cells, the finite current HR & IT resources would still need new methods to do the work in 500M cells per project. Each team member does not have and urgently needs a common denominator, to transform material worked and to be worked, such that each knows what others are doing, and the collective whole properly and harmoniously manage all risks.

Clastic and carbonate continental shelf sediments, compact (lose pore space) in burial, at relatively predictable rates, in the absence of locally anomalous stress, strain, temperature, pressure or fluid systems. See Figure 1. In such circumstances, as depth increases, sediment interval velocity Vint plus its rate of compaction are commonly expressed as Velocity at origin Vo plus associated compaction rate K, of Vint change per particular sediment lithology type, with depth.

So, in such cases, each of say 20 key lithologies behave with depth, in a manner where local Vint is a function of Vo + K, so lithology is quantifiable. This does not assist E&P efficiency much, because of potential for error in every place of different geology. See Figure 2. No rules and tools yet exist to quantify all such potential for locally different geology, or to use this difference to cross-correlate the 'normal' material, with the local geological circumstances, elsewhere .

23/04/2012 2 KA GeoDirk In, for example, Atlantic Margin sedimentary basins, oil and/or gas is produced from sediments ranging in age from less than 30million years, to some hundreds of millions of years. The sediments, increasing in age, are in the Quaternary, Tertiary, Cretaceous, Jurassic, Triassic, Permian, Carboniferous and Devonian, all of which may locally trap hydrocarbons. It is self evident that the various tectonic episodes of extension, compression, uplift and subsidence, in these periods, will have locally imprinted the geology of those sediments that exists at the time of the tectonic events. Therefore, older sediments may have many more such causes of normal and abnormal burial change, than younger sediments. Therefore, to mitigate against probability of wrong prognosis of current rock properties becomes more complicated, as one moves from younger to older sedimentary sequences. Therefore, sensible rules and tools are required, and these, hitherto, have been most incomplete.

Figure 3 summarises poro-perm behaviour of key lithofacies, with potential for one lithology to have similar poro-perms in different depth ranges.

Figure 4 shows that, by knowing +/- a few %, velocity interval Vint and depth, plus the depth difference between that and a generic normal material compilation, one can convert samples into the material to better quantify traps, reserves, recovery and risk. To do this requires 6 classes of work to be performed to prepare the following:

'Normal' model

Seismic for normalised G&G processing.

Geology.

Petrophysics .

Trap volumes .

Oil or gas fluid corrections & risk of overpressure.

The present invention constructs a depth based-cellular model of geophysical, geological and petrophysical parameters, derived from one geological 'generic normal' type of common burial setting, in a particular way such that seismic data.

23/04/2012 3 A GeoDirk where Vint and depth are quantified, can be converted into detail of lithology, compaction, poro-perms etc., in any similar circumstances of geologic burial conditions as well as in any other burial circumstances, where any difference between the depth normal and the depth of other per cell are also quantified .

The present invention also relates to the modification of seismic data to enable two operations. Firstly it generates new, extra material quantifying volumes of seismically homogeneous sediment and their boundaries. This is necessary for risk reduction of unquantified or wrongly quantified lateral or vertical changes in both sediment type (lithology) or burial-related compaction and digenesis. It also enables geoscientists to perform work in very small volumes of data, to QC, QA output of machine processing of large volumes of material .

Secondly, it prepares material essential for subsequent normalised depth modelling of geology and petrophysics , while concurrently quantifying and separating out geologically impossible data.

Seismic data (except pre stack depth migration) in oil and gas exploration and production commonly allows per unit space, geologically impossible geophysical (velocity, density) models to be derived. Seismic shows shapes based on velocity x density, in the form of changes in acoustic impedance. Sedimentary rock grain and matrix minerals have small density differences but velocity differences are larger. Pore fluids tend to have density of brine, fresh water, oil or gas.

Once seismic sequence boundaries are picked, the need is to derive velocity fields to allow depth conversion.

General Background

Subsurface information is mostly worked by multi- disciplinary asset teams, each using one of a few types of very similar IT workstations, where each project is worked without ability to quantify all relevant causes or effects of rock

23/04/2012 4 KA GeoDirk properties, (i.e. part subjectively) limiting capacity of any expert to understand or QC the whole work.

Seismic now is rarely worked at its trace sample resolution of say 2 milliseconds, into lithology, poro-perms etc. When this is done, it invariably requires use of well data from local similar (?) geology, and much iteration via inversion procedures, to then have 50% probability of being wrong in complex exploration projects.

A primary problem that has limited progress in this task area is the fact that at any elevation in sedimentary basins, between say + 2000 metres and - 6000 metres, per very similar rock deposit, or lithofacies type, most elastics (sands, shale, mudstones) and carbonates (chalk, limestone) commonly exhibit wide ranges of velocity, porosity and permeability. So, who can say what 'normal' behaviour is?

A good correlation is reported to exist between depth and velocity when material is compacted in a rock mechanics lab, or when it is compacted in much of the shallower areas of North Sea, Norwegian offshore or USA Gulf Coast. Here, lithofacies/ velocity/ depth/ poro-perm relationships are fairly robust, in the absence of cause to make this not so. Per lithofacies, all evidence suggests that permeability is a close function of porosity.

So, what is needed to cut risk of error, is a complete understanding of all such interrelationships in a particularly simple geological set of circumstances plus a set of rules and tools to enable quantification of any differences in geological circumstances per other project area, whereby such differences are particularly assembled to enable cross referencing between the norm and the local .

Procedures known as 'Becvem' and 'Spiral' go some way to address these background problems . Need 1 is to have a generic 'normal' geologic and petrophysical listing in depth, against which all other geological project data can be compared and information derived, instead of having to make from direct sensed data a different listing per different geological basin, and then have to construct specific methods to quantify any differences between that direct sensed model and all other remote sensed geophysical data.

23/04/2012 5 KA GeoDirk SUMMARY OF INVENTION

To overcome this part of the problem, the present invention provides the construction of a generic, normal depth based inter-relationship of key geophysical, geological and petrophysical parameters, structured such that, when seismic +/- well data is worked to quantify key geophysical and geological parameters per cell in any similar, the 'normal' burial area, (or any other abnormal burial area if the depth difference is known per cell between normal compaction and local actual compaction) , then the suite of geological and petrophysical parameters needed to quantify seals, trapped reservoir gross and net rock volume can also be quantified by referencing to the generic set.

The invention enables cross correlation between the normal model and any other E&P geoscience project model, in which seismic attributes and shapes are worked to define depositional rock type and its burial controls, including quantification of per cell of the maximum depth equivalent of burial, where the equivalent used is the generic normal set of parameters .

Then, per cell, per new project, the parameters used or generated in this conversion process include time velocity depth, acoustic impedance changes, lithology/ lithofacies, normal compaction plus the depth difference between normal compaction and local actual compaction, then poro-perms, pressures, fluids, temperatures etc.

Figure All-4: summarises key parts of the present invention and summarises where the extra work of the present invention fits within prior art workflows. Overall, it adds up to around 50% more work done per project, by machine batch processing, objectively, rather than heavily HR driven, subjectively. Further, about l/3^rd of labour intensive, prior art work is done by the new art, by machine in batch processing.

To overcome another part of the problem, the present invention modifies seismic data to generate new, extra material quantifying volumes of seismically homogeneous sediment and

23/04/2012 6 KA GeoDirk their boundaries, and separately it formats material for subsequent normalised depth modelling of geology and petrophysics , while concurrently quantifying and separating out geologically impossible data and volumes of seismically homogeneous sediment and their boundaries, to aid risk reduction of unquantified or wrongly quantified lateral or vertical changes in both sediment type (lithology) or burial related compaction and digenesis.

The present invention preferably uses filters, rules, algorithms and libraries of physical evidence and other means to do this, in a 3 -stage process, with two optional but preferable features. It reworks today's seismic mix of velocity, density, plus noise plus decaying frequency to isolate, quality control and quality ensure geologically sensible acoustic impedance and velocity output, then sequence selection and boundary picking thereof, using several material components, then seis-strat quantification thereof, such that conversion of seismic into all key geologic and petrophysical parameters can be effected by the G&G normalisation process.

The above part works seismic to separate all sequences (layers) of significantly different apparent seismic homogeneity, storing their time boundary information with velocity Vint, and depths. Also stored at seed points is material summarising character and pattern of seismic.

This data can be combined with geologic model data, such that geophysicists output apparent lithology and compaction and poro-perm material, in high resolution 2D sequence files, to confirm that it has good potential to make sense to geologists, and petrophysicists .

Subsurface information can be worked by teams and their existing IT workstations in a million cells/ km3 in projects >500km3 by objective methods and means, quality controllable by all disciplines, that are accessed and integrated to conventional work flow by a series of ^lAPS' or applications.

The addition of this capacity cuts subjective incomplete HR work unique to each project and replaces it with objective IT more complete work whereby upon quantification of key differences between the generic and new project models, IT machines work out almost all other material necessary to

23/04/2012 7 KAGeoDirk maximise resolution of all key properties and probability of correct prognosis.

This invention also addresses issues in the exploration or production geoscience environment, where the norm in 2010 is to be some 50% (E) and 25% wrong (P) , respectively; in respect of predicting lithology and poro-perms in at least some key project rock volume.

Workers with the material provided, for example, as a set of paper-based tabulations, can quantify the difference in poro-perms and lithologies, per unit depth, between the ⁴ normal' situation and the local, conventionally made prognoses, and know, to a large extent, that the reason for such difference if any, must be geological, or in the velocity field. They know how to double check the velocity field. If the local porosity is greater or less than suggested by the 'normal' data, they need to look for evidence as to why they have predicted this. Similarly, if the lithology conventionally forecast differs from that which is normal, they need to work the project material for evidence for why that may be so.

The present invention may include post stack / migration seismic processing, filtering and seis-strat processing, before conventional seismic sequence and geological and petrophysical interpretation, adds material relevant to partial and potentially fully automated conversion of seismic into all key geological and petrophysical parameters, while cutting risk associated with use of poor data or interpretation.

Preferably, the output includes initial models of sequence time, velocity, depth plus (assuming 'normal' burial) lithology and compaction. This allows risk reduction that velocity fields are badly done, or that 2 or more volumes of different, relatively homogenous rock types are treated as one sequence laye .

At minimum, the several extra displays of seismic aid workers to be sure they have correctly picked the necessary sequences. Beyond that, is provided a quantitative suite of parameters necessary for complete geological & petrophysical normalisation processing.

23/04/2012 8 KA GeoDirk BRIEF DESCRIPTION OF THE DRAWINGS

These relate to the construction of material comprising a generic 'normal' compilation in depth of geophysical, geological and petrophysical parameters for oil & gas E&P geoscience, for use to convert between this geology and any other project geology, an example of the invention will now be described by referring to the accompanying drawings :

Figure 1 shows that key lithologies, in common normal burial, should be quantifiable where seismic velocity data and depth are accurately known.

Figure 2 shows that complexities in burial act as pitfalls in predicting lithology from seismic velocity.

Figures 3 a-b show that per lithology, poro-perms are a close relation of each other, independent of depth of burial, only where burial is non normal.

Subsequent figures show preparation of material to effect

1, Figure Gl : Lithology can be forecast using depth & velocity, in any rock volume having similar burial conditions.

2, Fig G2 : porosity can be forecast using lithology & velocity.

3, Fig G3 : permeability can be forecast using lithology & porosity.

4, difference in burial conditions, can be quantified as a relative depth difference between a generic normal burial depth data set, and any other rock volume, where lithology, depth fluid and velocity are known, e.g. from well data.

5, Lateral rates of change, and minima and maxima, of seismic velocity &/or AI that are geologically implausible laterally and vertically, based upon information in local data are constructed, to allow filtration of seismic.

Construction of material from seismic, in projects of any oil & gas prospective geology, allows conversion to geology and petrophysical material via quantification of depth differences between a generic normal compilation and the local material, an

23/04/2012 9 KA GeoDirk example of the invention will now be described by referring to the accompanying drawings , in 5 parts :

Pre interpretation processing:

Work flow is to quantify sequences & material for normalised G&G processing.

la. From the surface to basement, net AI change /seismic trace is compared with the actual net change, known, reasonably from velocity x density in both places.

1. Trace samples are reduced to spikes, representing + or - changes in AI (velocity x density), net of wavelet.

2. Trace samples are worked to quantify amplitude, frequency and phase, and their differences.

3. Velocity time pairs used in processing are converted to interval velocity.

Groups of traces are worked to quantify seis strat parameters (extent of continuity, layering and divergence) and amplitude phase frequency properties.

Well data is worked to quantify sequences as all significant vertical changes in sediment homogeneity, and each their time, velocity, depth, lithology poro-perms, fluids and velocities .

The above material, by weighted integration, works to separate all significant units of relatively different homogeneity by sequence boundaries, first at seed points, then providing sequence shapes as 2D surfaces

For the purpose of calibrating seismic inter-sequence trace sample data, such sequences are mapped in time, velocity and depth. An initial geological model based around a known common set of properties per lithology (PPKA1) is constructed, to ensure data is geologically plausible. These components then provide output material necessary to allow later (PPKA3) processing of the effective depth difference between the initial geo model and the model best fitting the project data.

DETAILED DESCRIPTION

23/04/2012 10 KA GeoDirk Figure ALL-2 summarises general E&P G&G workflow, leading to efficiency noted.

Figure ALL-4 summarises key parts of extra rules and tools to increase E&P efficiency

A generic 'normal' (i.e. no burial anomalies) velocity/ depth model of key lithologies, and their poro-perms, in brine is constructed in such a manner to allow this to be applied to data from dissimilar geologic settings, where the relative depth of burial differences are known.

Fig Gl shows why key Lithologies (because of fan shape spread) are quantifiable from velocity depth material, potentially generated at high accuracy from seismic, if rates of compaction are locally known.

Fig G2 shows schematic of Porosity of key Lithologies as a function of generic normal depth. It may also be plotted against velocity, per lithology.

Fig G3 shows why key permeability (because of a different fan shape spread) is quantifiable from lithology and porosity, on a poro-perm cross plot that also quantifies seal/ carrier bed/ reservoir rock potential.

Figure G3 shows that per lithology, poro-perms are a close relation of each other, independent of depth of burial. To access this methodology using seismic Vint, one needs to quantify abnormal burial per sequence/ cell.

In any G&G work project in different geologic setting, that difference can be usefully distilled down to the difference in burial conditions, relative to the known data set. In the known data set must thus exist a sufficiently complete supply of material quantifying lithology, (better, lithofacies ) , and behaviour at all depth of all key petrophysical effects, that result from the one suite of geological burial causes in the 'normal area, Then, since the depositional & normal properties as varied with normal depth changes are already known, they can be effectively known anywhere else, if the difference in geologic conditions of

23/04/2012 11 KA GeoDirk burial are known and quantified as a relative depth difference, that cause changes in effects, (e.g. poro-perms) .

From the point of view of constructing means to handle these steps, the way this invention works is summarised as follows .

The material available with which to quantify poro-perms is seismic data, prepared by experts in the art (plus method A2011-2) as velocity interval Vint material, in depth, per seismic sample or cell. Then per Vint sample Sediment rock types (lithologies) are represented as velocity at origin Vo.

Per sediment lithology,

Normal burial circumstance increase in velocity with depth as represented as Kn. Any abnormality in velocity change with depth is represented as (+/-) Vint of Ka, where Ka is the local abnormality in compaction /digenesis.

Vint = Vo + Kn (+/- Vint of Ka) . So, if this is known, per unit space, the depth difference between normal and local can be materialised see fig 1.4

Figure 1-4 illustrates how known difference in burial conditions per sequence cell can be quantified as a relative

set, and any other rock volume, where lithology, depth fluid and velocity are known, e.g. from well data, and / or from seismic .

In 'normal' shelf burial, at around 3000m, see figure Gl, sediment basin rock types span the velocity range between that of water at 1470m/s to <6000m/s for some evaporates and igneous intrusions. In between these values, from slow to fast velocity are the elastics (fine grained to coarse, as shale, mudstone, sand) and carbonates (chalk, limestone), salt anhydrite etc. Sediments with no remaining pore space cease mechanical compaction, but may change chemical form. The rate of pore space reduction and velocity increase in normal compaction (Kn) and digenesis ranges from around 0.2m/s/m for shale, through >0.3m/s/m for sandstone, to >0.5m/s/m for chalk, until they are highly compacted leaving negligible pore space.

23/04/2012 12 KAGeoDirk This normal sediment compaction behaviour, given capacity of seismic data to allow quantification of depth and velocity at accuracy usually >97%, so any seismic cell or sample could be resolved at +/- better than 3% of say 3000m/s, i.e. 90m/s. In 'normal' shelf conditions, (steady vertical burial) there are 20 units of 250m/s between 1475m/s and 6475m/s, each representing a seismically resolvable 5% change in velocity.

Figure 1-1

As oil runs out in mature basins, price rises will increasingly push exploration towards less explored basins, where data concerning, per lithology, depth behaviour in respect of velocity, porosity, permeability etc is not fully sampled or known.

The prior art enables incomplete knowledge of depth/ lithology/ rock properties in any local standard geologic setting, plus incomplete capacity to quantify in space the causes and/ or effects of local changes in geologic deposition and/ or burial changes .

Using sample and cell velocity and depth material (prior art provided this at around 97% or better accuracy) , extra tools are also attached to the generic normal material to serve as follows.

If at a forecast space in depth, a particular velocity and lithology are forecast by prior art methods, the tool will quantify its porosity, permeability and potential as reservoir rock, seal or carrier bed. Further, the tool will state the extent by which the prediction of lithology by the prior art is necessarily associated with a particular burial depth difference, relative to normalisation with the normal data set, so that they can QC & QA their work, by examining evidence that causes of such differences probably exist.

Well data from a project can be plotted against the generic normal data set, to quantify the relative depth difference between the normal and local burial conditions. By this, is meant that a particular lithology with a particular Vint at a particular depth may or may not show a different depth for similar Vint, in various project samples, relative to the generic. It is this (delta) depth difference that is used to

23/04/2012 13 KA GeoDirk select sensible porosities for each sample lithology. This allows users of the prior art, where they perceive a cell space to have a particular velocity and depth, and to have been subjected to burial similar to the well, to convert that velocity and depth into lithology, porosity and permeability. This provides QC against methods of quantifying lithology and poro-perms from prior art methods.

Building the generic 'normal' geoscience material.

Primary deliverable, for normalised G&G processing of seismic, is material quantifying key properties in depth of key sedimentary rock types, i.e. lithologies, spanning all significant sediment behavioural property classes within a few %, such if any lithofacies is categorised as nearest one of the classes made, its properties will interpolated to be a close approximation of the class used.

Few overlaps occur at most depths at which shale is an effective seal, yet sands are viable reservoir rocks, in 'normal' burial. This tabulation needs to be adjustable by the depth difference between project sample data and the normal data used. Then, the particular local normalised depth and local cell Vint allow quantification of lithology and associated property parameters.

23/04/2012 14 KA GeoDirk

dolomite

Table G lists the properties required per sediment class, lithology, where behaviour is classified against depth, of velocity, porosity and permeability, where fluid is water, (or brine) at hydrostatic pressure.

Classification should use material from a basin with simple burial, with key clastic and carbonate lithofacies at depth ranges where porosity % varies from high to zero. Add information for sediments with evaporites, salt etc.

Fig 1.1, or Gl, shows velocity trends and K rates for key lithologies in such circumstances. The assumption made is that any lithological type set of mineral grains will change their velocity/ poro-perms to the same extent, at the same rate, worldwide, if then subjected to identical burial changes.

If data of a clean sand, shale or chalk plots other than on the line chosen, it does so because of differences in either deposition rock type is incorrect, or it's burial change is different relative to generic normal material, or because the data sample has errors. All such factors can then be quality controlled.

Material output from mechanical test lab work can be used to confirm changes in velocity, poro-perms, with depth and/ or pressure and/ or temperature. To make this material be accessible to material from other project data sets, it must plot parameters against depth, such that the parameters may be accessed where their present depth is known, and adjusted by addition or deduction of depth difference corresponding to the difference in burial between the local actual and generic normal material.

23/04/2012 15 KA GeoDirk The generic normal material is best generated by means that can work input material to quantify local presence of all causes of abnormal compaction and digenesis, and their net local effect. This allows normal material to be selected and used.

Primary deliverable data concerns the working of well data, from areas which may be other than the normal. A separate part of the invention is to construct means to correlate well data, from any sedimentary basin, constructed similarly to above, so that the local can be cross correlated with the generic normal, to enable relative differences in depth between the two to be quantified. This quantifies the difference in burial alteration of the sediment, per sample, in various places along well bores. This provides local calibration for other work with remote sensed data, between such areas with assessed well bores, when local project data may be modelled to be correlate observed geological causes of burial change with the resultant petrophysical effects.

Means to do this have historically been foiled by lack of definition of what constitutes 'normal geology' . We know normality in deposition of sediment lithofacies, (lithology & environment) . It is on or close to the surface we live on. Nobody has yet defined a type normal set of burial compaction/ digenesis, without which depth normalisation to allow seismic conversion to lithology & poro-perms is high risk and subj ective .

"The means to establish a generic normal set of burial changes exists in capacity by which abnormal burial compaction changes (Ka) are quantified at the resolution of seismic. By subtracting the particular abnormal, you are left with the particular normal. Fortunately, a particular normal is familiar to most oil & gas geoscientists . Shallow water shelf sediments, deposited and buried +/- vertically, in relatively steady state, minus compressive tectonic activity, structural or other inversions, igneous activity, or extensional thinning etc., are the norm, for many workers.

Means to construct the required material in the required manner then become obvious .

23/04/2012 16 KA GeoDirk Access per lithology, per unit depth, the well +/- lab material suggested above.

>10 examples, depth from surface to 0% porosity.

Separate out any lithology/ depth unit detail of velocity or porosity or permeability that is more than a very few % different from the average, then explain that difference.

In working ' 000's of km of well bore data representing all lithofacies types, we know the retrospectively obvious fact that any lithofacies deposited similarly anywhere in the world, will +/- very few %, have similar current buried velocity / poro-perm properties, if buried/ compacted/ changed by very similar conditions. Differences from the evolving norm should emerge, explicable by non normal burial changes.

Definition of lithology via charts suggested in Becvem & Spiral methods, was closely based on methods used by Gardner et al, then largely unused, for reasons given in their patent specifications .

An anomaly was suggested to exist, in that at some 1400m normal depth equivalent, sands and shale were suggested to offer zero A.I. contrast. Detail worked and published in Norway before 2009 confirms our work. We examined seismic recording some several thousand km3 of clastic sediment in this depth environment, and found no evidence of any such of A.I. absence. This suggests to us that sands and shale offer A.I. contrast, as do water and gas sands. Since gas penetrates upwards unless sealed, e.g. by shale, one cannot postulate that the [water wet] sand & shale have no contrast, but that water & gas wet sands do provide the contrast. The Norwegian studies show clastic sediments when shallow, in shallow water, seem to slow their rate of compaction relative to lab work, and work by Gardner et al .

Such charts are now made and applied in 2 stages or editions. A second edition is derived based on charting lithologies via porosities, via grain, matrix, colloid densities, plus porosities plus fluid densities.

Previous methods and means were applied to seismic sequences. Present and future economic needs require seismic to be processed into rock properties at seismic resolution. Since

23/04/2012 17 KA GeoDirk 2D, 3D seismic is based on acoustic impedance differences between layers, not necessarily all picked as sequence boundaries, and since such information is a product of velocity x density, need exists to build and use charts based on velocity, and depth, derived from velocity and density behaviour, as above summarized, and as already known by experts in the art .

First stage charts allow apparent geology to be approximated .

Examples of lithologies, in reducing velocity order, see Table G-Lith are Anhydrite, Dolomite, Evaporite, Limestone, Salt, Chalk, Sandstone, Mixed clastic, Shale, Over pressured shale, before water.

Resolution is possible to subdivide velocity range from 1500 to 6500m/s @ 3000m depth, into > 16 lithologies.

Definition of porosity via charts was suggested in Becvem & Spiral methods, without specification of how such charts should be generated, except that they should work, by extending the methods widely used in working electric log data to the seismic method. We have found that methods specified as examples in attachment works effectively in thick sequences of one homogenous litho-facies , but does not, where inter-beds occur of different litho-facies .

Methods are hereby provided to allow material output concerning potential for such inter-beds to occur and their litho-facies and porosity-permeability.

The structure suggested earlier should, in practice, allow users to fine tune values and relationships.

Oil / gas fluid differences relative to brine are data based for access to the Fenda operation per lithology, per unit depth, variable according to hydrocarbon type, density, saturation, and net probable effect on rock velocity.

Per lithology/ depth unit/ normal burial, is added to previously defined material (velocity, poro-perms etc,), enough material to quantify source potential.

23/04/2012 18 KA GeoDirk To more completely quantify source lithofacies potential, one may calculate pressure and temperature during historic time and depths in burial. One can then estimate fluid type, richness and maturity per cell. One can use this to support later tasks of work.

See Table G-HRQC

All the team can thus understand & qc how seismic best

Concerning the modelling of seismic into geology, there are four stages of methods and means required to construct the primary deliverable.

Work stage 1 processes lithology and compaction, assuming burial/ digenesis is as per normal. Normal here includes fluid brine fill.

Work stage 2 filters stage 1 seismic and G&G material for material separately providing evidence that model 1 G&G is locally wrong.

Work stage part 2 constructs evidence of net change per cell, of all separate causes, at sequence vertical resolution, within the velocity depth domain, and converts this into a depth adjustment, positive or negative, in fit relative to the generic norm.

23/04/2012 19 KA GeoDirk Work stage part 3 converts project data into geology at sequence resolution, optionally linking with default systems to minimise risk that lateral and vertical variations in the geology are improbable.

Work stage 4 converts the above at trace sample resolution, with time averaging, to ensure that sequence thickness is proper, and that all sub sequence units are proper in respect of their time, velocity, depth, lithology Vo, Kn & vint of Ka.

Preparation of 2D, 3D Seismic for normalised G&G processing.

The essential technical features differentiate in space seismically resolvable homogeneous rock volumes by processes that format resultant material (attributes, shapes) for resolution of depositional form and lithology and their response to quantified burial changes, to later understand compaction and digenesis. A key product is robust conversion of seismic into pseudo sonic velocity traces, for proper depth imaging and geologic, petrophysical and reservoir engineering studies .

These features exist in 6 parts.

Attribute System. Key attributes are digitally represented, per trace sample and groups of seed traces . Well data and seismic processing velocities are added.

Construction, & QA, QC systems.

Seismic trace samples are quality controlled to monitor fair representation of vertical and lateral gross and net velocity, density changes between surface often under-compacted, and basement fully compacted, using new rules and tools.

Seismic trace data is processed to separate out volumes of similar homogeneity and their boundaries, on the basis of amplitude and frequency +/- phase.

Seismic Vrms or Vnmo or migration processing velocities, as available, are quality controlled to monitor their being not geologically impossible, against a sub set PPKA/1- 1. These are converted to interval velocities Vint and each change supplied is processed to show locations of values and their differences.

23/04/2012 20 KA GeoDirk Seismic stratigraphy is processed from in running small groups of traces, so to separate rock volumes of different seis strat pattern and character.

Sequence definition: Compounding Mechanism. A weighting mechanism works 2) a-d material above into a compound. Different weights applied to these parameters provide serve different quantification of sequence layers and stratigraphy, as geology and data acquisition parameters vary.

Seed Point Interpretation. Traces are gathered at 'seed points' at which seismic sequences are defined where each sequence and their boundaries provide statistics defining their presence. Integration of well data provides primary seeds. Integration of seismic processing velocity data provided secondary seeds. Tertiary seeds occur every few hundred metres. 4^th level seeds occur at each trace.

Sequence Geometry Interpretation. This is achieved by integrating a best geometric fit between 2^nd level seeds with 1^st, then 3^rd, then 4^th. The statistical evidence of homogenous layers and their boundaries provides hypotheses why particular geometric boundaries may exist . Seismic event tracking is used to test these hypotheses. Rule based fault control modelling is applied to aid correlations .

Trace calibration using initial geologic model.

Risk Analysis system.

Experts in the art know how to assemble well, seismic velocity & trace data, and quantify trace, character, amplitude, phase, frequency, plus seis strat pattern from groups of traces . What has not been done before and should usefully be done is to scale these parameters such that at any chosen seed trace or group of traces, it becomes possible to better/ faster separate most likely sequence boundaries between volumes of relatively most homogenous sediments . When this is done at enough seed points, using statistical processes known to experts in the art, it is possible and useful to best fit i.e. join up such seed point suggested sequence boundaries, into 2D vertical surfaces and then 3D data sets.

23/04/2012 21 KAGeoDirk The bottom right box in Fig 2:1, seismic data prep below, then summarises work done to convert such sequence information into a viable geologic model, assuming Part 1 normality of burial conditions .

Fig 2:1 seismic data preparation, summarises actions.

Part 2.1 Attribute System

Filters are made by means known to experts in the art, that withdraw material summarized in tables 4 & 5. Such material output is newly combined into assemblages of material by further new processing using weights set by the processor.

The filtration is applied initially at seed points, being groups of seismic traces . Such enables this work to be performed by new means that allow a standardization of classification of attributes, used in processing of attribute pattern, character and net relevance, so to allow layers (sequences) to be isolated together with detail of lateral and vertical variations, relative to the standard applied. Material so generated is then re-applied to seismic vertical cross sections and vertical maps, using gridding and contouring to separate zones of like characteristics.

Specific examples of the invention will now be described by way of example with reference to the accompanying drawings and table in which the figures show the material used and the order of use.

See Table 2-1

23/04/2012 22 KA GeoDirk Amplitude, value &

changes

Phase value &

changes

Frequency value &

changes

Continuity

Layering

Divergence

Extent chaotic

Chrono offset class

Velocity, interval,

wells

Velocity, interval,

seismic

Iteration lithology, Trace samples Per cell space

Vo, K, depth

Cause controls on

sequences

Rock properties,

poro- perms

Pseudo grav- ag

A.I. as velocity &

density.

Re-iterate whole

model

Seismic Interpretation pre processing.

All traces

23/04/2012 23 KAGeoDirk Statistics on net AI change, per trace, per line & per survey. This represents net changes in velocity times density, between top & base of recording. This provides a measure of polarity and allows correlation between probable and observed, from which scaling [e.g. gain] can be adjusted.

The following hypotheses are used to constrain the following tasks ;

Quantifiable seismic behavioural assemblages tabled above constitute >16 factorial [161= >20,000 billion] possible combinations of seismic 'appearances' by which the art now of expert HR works out seismic sequences and their boundaries, using seismic data. (N.B.: 6! =720 classes). Attempts to systematize solutions to enable seismic sequences and their geometry to be machine picked, by applying various weights to the criteria available as data/ cell, have low probability of success & no machine solutions are yet in commercial use.

The present invention approaches this problem from the opposite direction. The primary need today is to identify depositional environment and its relative spatial changes.

Compounding Mechanism. Establish weighting mechanism, table 4, whereby seismic can be worked in a domain representing a compound of such key attributes, and where the constituents of such compound are identified, and variable by default mechanism. Attributes are based on amplitude, phase & frequency, and on seis strat pattern and character. Different combinations of these attributes may best be used to identify sequence layers and stratigraphy, as geology and data acquisition parameters vary.

The present invention uses already derivable data/ cell [table 4] to derive data about apparent lithology & environment by cross referencing with material stored from PPKA1. Then, as a bi-product, this serves new ways to process sequence geometry.

The present invention works as follows;

Prior to generation of seismic sequence boundary material, to work seismic attributes, properties, character and pattern, velocities, or other remote sensed data, at trace sample location, per grid cell resolution.

23/04/2012 24 KA GeoDirk Seismic sequences and their geometry in time.

Experts in the art can already build systems built from public domain methods and means to scan and classify the detail of the seismic and its attributes. The present invention provides for

Use of specific filters and algorithms and data bases can work seismic trace data as above, and calculate a best fit between apparent geology and data resolution.

Use of specific filters and algorithms and data bases that can be set as defaults by processing of the input seismic data into this information, risk and knowledge elements, via models used to remove information of high risk, and classify all information in terms of risk, relative to model.

Seed Point Interpretation. Test such systems and default settings, to generate at seed points a facsimile of seismic sequence definition, where such constituents of the compound also contain seismic stratigraphic information.

At seed points, [e.g. half km2?] . Gather work attribute system material, groups of seismic reflection [2D, 3D] Pwave traces, & processing velocities. See table above. Each sample holds wavelet plus attributes [phase, frequency, amplitude] . It is worked to show relative continuity & divergence, and wavelet, then attributes minus wavelet.

Assemble 3D volume of grid-cells, this material, & process and, by these means, each geo-cell is hereby enabled with two components of material : -

The attributes normal to geophysical interpretation of apparent geology, and

The attributes not normally used in geo- interpretation, but which are manufactured, such that they may be constrained to behave in a geologically possible manner, applied in a new environment, at the resolution of seismic samples (2 to 4 milliseconds), treated as pseudo- sequences .

Groups of traces at seed points (Table 4 data) are processed such that at each sample is manufactured as per Table 5 :

23/04/2012 25 KA GeoDirk tasks Vertical Lateral changes metho changes d

Per trace & group

per trace traces

Low Well data as as sequences

frequency available giving weight to

seismic derived

DIRK.

Filter for *

Processing

velocity & its

change

Medium Continuity & *

frequency its change

lateral

Divergence & *

changes .

its change

Filters

Dip angle &

direction

Spatially

limited

horizontal

events ,

terminating

lower events,

by A, F, P,

dip .

High Velocity * From AI.

f equency change . From Density here

well data and deemed

seismic AI . proportional to

V.

A. Amplitude & *

its change

F. Frequency &

its change

23/04/2012 26 A GeoDirk

change

From these ingredients is compounded a numerical pattern, varying by value and lateral and vertical changes and component causing such changes. From this, vertical gates are generated of material, spanning each trace sample.

The material above is examined, whole data set, to provide material defining statistics concerning average behaviour, minimum and maximum changes , such sample to sample changes can be expressed as % relative change, relative to overall behaviour of a particular parameter attribute, within the project data set. This also can act as a step to allow reprocessing of such material to adjust gain etc. This generates material relevant to machine determination of units of like and nonlike rock properties, as in lithofacies.

The process defined at this stage in the overall thus derives material evidence of relative behaviour, then relative changes, first per attribute type, then in an assemblage of attributes. The assembly is drawn and weighted according to values manually set in a default system.

From this, each seed point trace group is processed to isolate some 50% more than the default selected number of seismic sequences, on the basis of the above parameters generated and & weights chosen. This provides material allowing processing output of area volumes of relatively like behaviour, based on the attributes used, via the weight assemblages used. Prior art works to isolate the bounding edges of sequences, subdivided vertically, defined as units of relatively homogenous material, bounded top and bottom by unconformities or correlative conformities.

Within a rock column often more than 6 seconds, 2 way time, per seed, [per group of seismic traces] may exist several km of sediment and some km of basement rocks. Need exists to differentiate basement from sediment and isolate probable sedimentary sequences. Basement is isolated by a default- imposed cut off in key criteria maximums of low and high frequency criteria. Basement occurs at depths where rock

23/04/2012 27 KA GeoDirk density is about 2.65, and velocity is >6000m/s, providing parameters allowing such quantification.

Within the probable sediment section, above basement, a default choice of say 12 vertically separated sequences to be processed, would result in processing of all possible sequence boundaries, where one or more of the criteria classes above provided reason. Weighting is applied proportional to the vertical distance from a probable sequence boundary. This constrains the method from 'bunching' of sequences.

To this is added means to perform by processing, to output material to isolate vertical boundaries, and also area volumes where material suggests general homogeneity. A weighting process numerically classifies the material assembled. Large Changes, vertical or lateral, are made materially evident, by subtraction, and then visualized by contouring. Seed point data so processed is displayed on seismic cross sections at seed point locations in a manner suitable for machine processing interpretation, and manual interpretation and / or manual quality control of machine processing.

Where a need exists to use material (attributes) at grid cell locations, the method allows such material to be processed at seismic trace samples, within a grid cell, such that the

TTiAO r*nmmnri npa i

together with material defining the proportion of the most common to other material. Where a need exists to use the material attributes for human visualisation, the method allows choice to be made of individual or combined attributes, or weighted group attribute detail of a multi level comparative. The method allows for such weighted group attribute detail to be 'balanced providing spatial correlation.

Quality Control

The input material is expected to contain parts of unacceptable quality. The methodology first constrains material to represent what is possible, then moves such material into a domain of relative percentages. Each commercial project may average 2000 seed points. This methodology provides a statistical base of processed material examination of which is relevant to quality control and risk analysis

23/04/2012 28 KA GeoDirk Risk Analysis

Material is stored per seed point per trace group per sample and thence to sequences, or the fit.

Sequence Geometry Interpretation.

Tests such systems and default settings, to generate at a facsimile of seismic sequence definition, where such constituents of the compound also contain seismic stratigraphic information. Includes dealing with lateral alterations in geometry, geology by faulting, or structural control. The extent of any grid cell material change, to become process output, is recorded for risk analysis processing. From this material, at seed points, processing is of machine top default 20 (x 1.5) sequences. Each has a multi level comparative.

Seed Points every approx. 1km interval, may normally be at seismic velocity processing locations. Action is to process correlation best defining boundaries of relatively homogenous units, using variable weighting, via known methods to output a parameter set, with numerically defining why this choice exists. Action then is to halve distance/ interval horizontal, and reiterate the process. Means are constructed to allow best fit correlation using known methods between the secondary & tertiary seeds. Action then is to halve distance/interval horizontal, again, and repeat until correlation exists at the required resolution.

Quality control

This method includes DIRK work and assembly formatted for statistical analysis of fit. It also allows the multi-level comparative to be plotted on section for visual QC by expert HR.

Risk Analysis

Fit between output data SI & output data S2 is derived as a measure of probability of correct prognosis.

Faulting

This processing system provides lateral correlation in gated windows between input material and output material. Since

23/04/2012 29 KA GeoD^'irk the output of SI processing is the input of all other tasks listed below, probability that it is correct needs to be deduced and monitored.

The above part works seismic to separate all sequences (layers) of significantly different apparent seismic homogeneity, storing their time boundary information with velocity Vint, and depths. Also stored at seed points is material summarising character and pattern of seismic.

The following procedure works the above data with normal geologic model, such that geophysicists output apparent lithology and compaction and poro-perm material, in high resolution 2D sequence files, to confirm that it has good potential to make sense to geologists, and petrophysicists . A primary objective is to prepare seismic to allow conversion of traces into pseudo sonic log velocity Vint data. This requires calibration at sequence boundaries using time, velocity, depth material, after their interpretation done in a manner reducing risk that significant volumes of different homogeneity remain un- separated.

Effective depth conversion of seismic sequences requires use of at least a basic geologic model, of depositional lithology plus normal and locally abnormal compaction.

According to the present invention there is also provided a processor equipped for receipt of the various types of input material prepared as above, to then process an initial such geological model, to permit a first stage sequence based depth conversion.

'Normal⁷ Geology compound system.

Map probable apparent geology (based on generic normal from above in sequences provided, at resolution between 100m2 & 25m2. Derive and record differences between generic normal defined apparent lithology and well derived lithologies . Constrain velocities (minima, maximums, gradients) to represent what is possible for the apparent lithologies and depths, recording adjustments made.

23/04/2012 30 KAGeoDirk Conversion of sequence Vint velocity fields to Vo + K, based on geo model above .

Specific examples of the invention will now be described by way of example with reference to the accompanying drawings in which the figures show the material used and the order of use .

Figure 4a, to process geological cause controls, evolving parameters, via input material and direct sampled material.

Table 1 summarises most of the overall work flow required, PPKAl-6, of which PPKA2 includes tasks 1-12.

TABLE 1 Cell data GeoModel, G&G

Items

Data Work System Method Metho | Metho Method 2 @

1-45 1 d 2 d 2 Resolution seismic

WorkFlow Etiect Cause Etrect

1. 2.

Attributes, Hard 1 well logs +/- cores, ID data inc

2 sonic, s wave,

( ciio-L , j- . j.ua j

3 GIS, cultural,

regional reports

4 Seismic, c wave pre

& post stack

5a# # *seis-strat

processing

5b# Seismic s wave

5b# P wave Attribute

versus offset

5c# Gravity & magnetic

data .

Fuzzy 3D 6# # *Sequence geometry,

23/04/2012 31 KA GeoDirk Properties time, 2D, 3D,

velocities & depth conversion

Relate Attributes Resolution indicator / sequence

[5-12 Apparent Lithology 8. litho- geology] facies 36

[13-18, apparent Maps porosity, total

& effective reservoir Maps permeability

engineering]

Map seals,

reservoirs n/g, &

deltaD.

Pseudo grav mag QC

ACE Balance Re-iteration rebalance as necessary

Trap maps : depth & delta D, GRV

Fluid type,

richness, maturity

Fluid fill,

migration loss

Map fluid contacts, connectivity

Connate water

saturation

Expansion factor,

capil press curves

Reserves in Place,

RF. , R I P

23/04/2012 32 KA GeoDirk 3D causal 19 deposition,

controls Lithology

20 deposition, Sediment

Environment

21 deposition,

structural setting

22 deposition, litho- facies

23 burial , Normal

Overburden weight

24 burial, Overburden

density adjusted

25 burial, Overburden

age adjusted

E1P1 risk 0.587926 burial, non vertical

stresses

E1P1 waste 41.20727 burial, structural

inversion s/w

$/b 5.769 28 burial, structural

inversion 1/w

add for slope

compaction etc see

PPKA3

29 burial, fluid &

pressure adjusted

E2P2 risk 0.705330 burial, temperature

adjusted

E2p2 waste 29.46431 Net Burial

Normalised

4.125032 lu AG = D + B + R

9

33 AG - R = D + B = G

23/04/2012 33 KA GeoDirk Apparent Geology compound system .

Map probable apparent geology in sequences provided, at resolution between 100m2 & 25m2. Derive and record differences between Generic normal defined 'apparent' lithology & properties and as they are when scaled to local project well data. Constrain velocities (minima, maximums, gradients) to represent what is possible for the apparent lithologies and depths, recording adjustments made.

Definition of lithology via charts suggested in Becvem & Spiral methods, was closely based on methods used by Gardner et al, then largely unused, for reasons given in those patent submissions. An anomaly was suggested to exist, see Fig Gl, in that at some 1400m normal depth equivalent, sands and shale were suggested to offer zero A.I. contrast. The inventor has examined seismic recording some several thousand km3 of clastic sediment in this depth environment, and found no evidence of any such of A.I. absence. This suggests that sands and shale offer A.I. contrast, as do water and gas sands. Since gas penetrates upwards unless sealed, e.g. by shale, one cannot postulate that the [water wet] sand & shale have no contrast, but that water & gas wet sands do provide the contrast. Further, as tar as the inventor is awax'e, nobody has defined or uses a generic normal oil & gas, geo/ petro set of materials. What is normal? This has to be defined first, and normal in one sedimentary basin is not normal in many other basins. This is dealt with above.

Such charts are now made and applied in 2 stages or editions. A second edition is derived based on charting lithologies via porosities, via grain, matrix, colloid densities, plus porosities plus fluid densities. Previous methods and means were applied to seismic sequences. Present and future economic needs require seismic to be processed into rock properties at seismic resolution. Since 2D, 3D seismic is based on acoustic impedance differences between layers, not necessarily all picked as sequence boundaries, and since such information is a product of velocity x density, a need exists to build and use charts based on velocity, and depth, derived

23/04/2012 34 KAGeoDirk from velocity and density behaviour, as above summarized, and as already known by experts in the art.

First stage charts allow apparent geology (i.e. as if in 'normal geology as per Part 1) to be approximated. From this, other processes allow the detail relevant to choice of second stage chart selection to be made.

Here is included a mechanism for a 2 stage approach.

Definition of porosity via charts was suggested in Becvem & Spiral methods, without specification of how such charts might be generated, except that they should work, by extending the methods widely used in working electric log data to the seismic method. The inventor has found that a method specified as examples in attachment works effectively in thick sequences of one homogenous litho-facies , but does not, where inter-beds occur of different litho- facies .

Methods are hereby provided to allow material output concerning potential for such inter-beds to occur, and each their litho-facies and porosity. The structure suggested earlier, should in practice allow users to fine tune values and relationships .

Apparent geology

Process Tree

Inputs Data to 2-2, from 2-1. This data comprises the following

TRACE) Seismic Trace Data, VSTACK) Seismic Stacking Velocities, TIME) Time Interpretation, WELLS) Wells, FORMATT) Format Time Data, FORMATV) Format Velocity Data, Seeds- character, Seeds - pattern. Input links to Part 1- normal lithology/ depth data material

(WB1_IN) Data In

(WB1_P1) Time maps & qc

(WB1_P2) Depth Conversion (1) grid seed velocities, convert vrms- Vint- Vo+kn from Part 1, work seeds only

23/04/2012 35 KA GeoDirk (WB1_P3) Lithology (l) check at seeds, that lithology is possible, if not probable.

(WB1_P4) Compaction (1) check at seeds that compaction of lithology is possible, (wide default setting)

(WB1_P5) Normalised Velocity (1) at seeds, re-compute Vo-t-Kn if necessary to make possible

( B1_QC) Quality Control at seeds, allow part 1 defined spatial grading of different lithologies.

Tie well data in well seeds

(WB1_P6) Lithology (2) at all sequence traces, rework as above, from depth con to lithology

(WB1_P7) Compaction (2) at all seq. traces, compaction Kn

(WB1_P8) Normalised Velocity (2) at all seq traces, Vo +Kn

(WB1_GRID) Gridding grid trace data to cells

(WB1_P9) Depth Conversion (2) depth convert all cells

( B1_ ELL) Tie to Well Information retie to well data seeds to ensure no errors made in gridding

(WB1_L0G) prepare initial pseudo comp Log data

(WB1_RISK) Risk Analysis

(WB1_0UT) Data Out

In Wb 1 seismic and well data can be displayed as apparent geology [Lithology, compaction, velocity, time, and depth] , probability of correct prognosis, in more detail, at sequence resolution.

Figure 2 shows where every seismic trace is worked. The intra sequence variability of AI changes/ Vint/ lithology/ poro-perms are mostly functions of inhomogeneous sequence lithologies.

23/04/2012 36 KAGeoDirk Need exists for the disciplines of G&G to be led to understand the whole of part 1 & 2-6, to ensure QC & QA. See Table G-HRQC

23/04/2012 37 KA GeoDirk

Claims

1. A method of oil and gas exploration and production which includes the construction of a generic, normal depth based inter-relationship of key geophysical, geological and petrophysical parameters, structured such that, when seismic +/- well data is worked to quantify key geophysical and geological parameters per cell in any similar, the 'normal' burial area, (or any other abnormal burial area if the depth difference is known per cell between normal compaction and local actual compaction) , then the suite of geological and petrophysical parameters needed to quantify seals, trapped reservoir gross and net rock volume can also be quantified by referencing to the generic set.

2. A method as claimed in Claim 1, which includes the use of means to reference and equilibrate, in terms of abnormal burial depth difference and /or interval velocity difference, each set of well data, per sequence, per oil or gas exploration or production project, to a generic normal burial data set, or to one key project well which is referenced to a generic normal burial data set.

3. A method as claimed in Claim 1 or Claim 2, which includes the use of means to quantify and quality control causes of inter-well, lateral changes in lithofacies.

4. A method as claimed in any one of the preceding claims, which includes the preparation of seismic data to be then made into an effective seismic sequence geological and petrophysical model, based around sediment properties, that are geologically probable, assuming burial changes similar to that controlling the generic normal burial data base, or the project key well, with or without other wells, being adjusted concerning burial changes to that key well.

5. A method as claimed in any one of the preceding claims, which includes the generation of an effective Vo + K sequence velocity model, for depth conversion, using well data.

6. A method as claimed in any one of the preceding claims, which includes ensuring that a geologic model is proper, relative to a defined 'normal' geo/ petro model.

23/04/2012 38 KA GeoD^'irk

7. A method as claimed in any one of the preceding claims, which includes processing of seismic shapes and attributes which later allows quantification of the separate and net collective geological and geophysical changes caused by burial changes, that may or may not be abnormal relative to well controls .

8. A facility for oil and gas exploration and production which includes means for the carrying out of the method claimed in any one of the preceding claims.

9. Means for the production of a depth-based tabulation of sediment rock properties, compiled in one generic oil & gas basin setting, structured to enable conversion of seismic, from basins of any structural or sedimentological history, into properties quantifying seal, reservoir and carrier beds, when keyed, per seismic trace sample, with local current burial depth and the depth equivalent adjustment required to quantify compaction/ digenesis differences between the generic model and the local model .

23/04/2012 39 KA GeoDirk