Showing posts with label geoscience. Show all posts
Showing posts with label geoscience. Show all posts

Monday, 5 May 2014

Wireline Logs


Well logging is an interesting method that deals with the subsurface layers providing every necessary detail required about them. The process basically involves specialized tools which are sent down through the well bore to gather the information about the subsurface properties. This data collected is represented over a series of measurements covered over the depth range of the well bore and this assimilation is collectively known as well logs.

The first well log was made in 1927 at Pechelbronn Field in Alsace, France. Invented by the Schlumberger brothers, Marcel and Conrad, the tool measured the electrical resistance of the earth’s subsurface. They recorded the data at each meter as they retrieved the sonde, a specialized tool suspended from the cable, from the borehole. This data log of the corresponding resistivity change was used to identify the location of oil.
The well logs are useful in defining a number of parameters that include physical rock characteristics, lithology, mineralogy, pore geometry, porosity and permeability. By interpretation of the well log data we can also estimate the productive zones with their thickness and depth by defining the basic parameters like fluid composition and relative saturation. The other prominent methods that involve the well data is relating them to seismic to obtain a proper correlation pattern that will help in confirming the hydrocarbon presence.
For oil and gas prospecting the well data helps in the rock type identification of geological environment, reservoir fluid contact location and fracture detection. One can also estimate the total hydrocarbon in place along with the recoverable hydrocarbon. Determination of water salinity, reservoir pressure, porosity or pore size distribution is also done with its help. The other properties that can be interpreted from the data are water flood feasibility, reservoir quality mapping, interzone fluid communication probability and reservoir fluid movement monitoring.
Applications of well logging data differ according to the specified specializations.
For the Geologist:
1.Depths of formation tops.
2. Geological environment and hydrocarbon accumulation.
3. Presence of hydrocarbons and its quantity.4.What are the reserves?
5. Conditions for an offset well.
For the Geophysicist: 
1.Predicted formation tops.
2. Potential zone analysis for properties such as porosity as assumed from seismic data.
3. Analysis of synthetic seismic sections.
For the Drilling Engineer:
1.Hole volume for cementing.
2. Presence of any Key-Seats or severe Dog-legs.
3. Location for a good packer seat for testing.
4. Location to set a Whipstock.
For the Reservoir Engineer:
1.Thickness of pay zone.
2. Homogeneity of the section.
3. Volume of hydrocarbon per cubic meter.
4. Duration of well pay-out.
For the Production Engineer:
1.Determination of well completion zones.
2. Expected production rate.
3. Chances for water production.
4. Suitable well completion methods.
5. Determination of hydraulically isolated potential pay zone.

2. Methods of Logging

Open-hole Logging

  • Performed on a well before the wellbore has been cased and cemented.
  • Logging is done through the bare rock sides of the formation.
  • Common type of logging method because the measurements are not obstructed.
  • Done during or after the well has been drilled.
Cased-hole Logging
  • Retrieve logging measurements through the well casing, or the metal piping that is inserted into the well during completion operations.
  • Cased-hole logging is performed more rarely but it provides valuable information about the well.
This chart is separated into three concentric areas: the middle annular area indicates the subsurface properties to be evaluated, the innermost area indicates the specialized logging tools, and the outermost area indicates other logging tools.
This chart is separated into three concentric areas: the middle annular area indicates the subsurface properties to be evaluated, the innermost area indicates the specialized logging tools, and the outermost area indicates other logging tools.

3. Log Types

The following are the most important type of logs:
1. Electric logs – self potential, resistivity and conductivity logs. Electric logs were the first type to be employed in petroleum exploration, because it was fairly simple to make the measurements. This involved measuring the electric resistance (R) (resistivity) and the current that is set up between the drilling mud and the porewater in the rock (formation), i.e. the self-potential (SP).
2. Radioactivity logs - gamma ray and neutron logs. Gamma logs measure the natural emission of gamma rays from rocks in well. A neutron log is obtained y using neutron source which sends radiation into the rocks. The absorption, mostly by hydrogen atoms, occurring in water and hydrocarbons is then measured.
3. Acoustic (sonic) logs – measure how fast sound travels through rocks, and in particular provide information about porosity. This also indicates whether a liquid or gas phase occupies the pore spaces.
4. Dipmeter logs – a type of electric log which measures the slope of beds and lamination in rocks.
Logs which directly measure properties of the well itself:
Caliper logsregister variations in the diameter of the well.
Temperature logs record borehole temperature and can be used to calculate the true formation temperature.
Image logs provide a picture of the well wall and may reveal layering, sedimentary structures and fractures
sp log

3.1. Electric Logs

Spontaneous Potential
  • SP logs record the electrical current (in milivolts) that arises due to salinity differences between a salt water based drilling mud and the fluid in formation.
  • Indicate permeability of rocks by measuring voltage difference between the drilling fluid and formation water.
  • Can distinguish shale from carbonates and sandstones.
  • Porous sandstones with high permeability generate more electricity than shale
  • Shale positive; sand negative.
  • Shale has values between 0 to -20 mV, sandstones and carbonates typically have values between -20 to -80 mV.
  • Identifies permeable zones and boundaries
  • Not good indicator of lithologic boundaries.
Typical responses of the SP Log
Typical responses of the SP Log
Permeability recognition by SP Log
Permeability recognition by SP Log
resistivity log

Resistivity Log

  • Resistivity is the physical property of a formation which impedes the flow of electric current.
  • Distinguishes type of fluid; hydrocarbon, fresh water and brine
  • Measures the effectiveness of rocks in conducting electricity
  • Short penetration reflects drilling mud; longer is due to formation of water
  • It is base on Induction Principle.
  • Low resistivity means shale/ wet sand; high resistivity means hydrocarbons
  • Resistivity is measured by drilling tools like DLL, HRI, HRAI etc.
  • Application:
  • Determines the true resistivity of formation
  • Indicated presence of movable hydrocarbons
Typical Resistivity Log Response
Typical Resistivity Log Response

3.2. Acoustic Logs

  • Petroleum applications of acoustic-wave-propagation theory and physics include both:
    • Surface-geophysical methods
    • Borehole-geophysical methods
  • Measures a number of sonic parameters like compressional & shear velocities and travel time.
  • Determines porosity by measuring the speed of sound waves in the formation.
  • Identify zones with abnormally high pressures.
  • Identification of gas-bearing intervals.
  • Estimate rock permeability.
  • Cement Evaluation.
  • Improve correlation and interpretation of seismic records.
  • Help in identifying lithology and fractures.
  • Helps in Geophysical Interpretation like Synthetic Seismograms, VSP, AVO Analysis, etc.
  • Study of rocks mechanical properties and acoustic impedance (in combination with the density log).
  • Displays travel time of P-waves versus depth.
  • They are recorded by pulling a tool on a wireline up the wellbore.
  • Tool emits a sound wave that travels from source to the formation and back to the receiver.
  • Tool measures the time it takes for a pulse of sound to travel from a transmitter to receiver. Both of which are mounted on the same tool.
  • The transmitted pulse is very short and of high amplitude. The wave travels through different forms like dispersion and attenuation occurs.
  • When the sound energy arrives at receiver, it captures them at different times in the form of different types of waves.
  • Travel time is the difference in the arrival of compressional waves at the receivers.
Typical responses of the Sonic Log
Typical responses of the Sonic Log
Log presentation for the GNT Tool
Log presentation for the GNT Tool

3.3. Nuclear Logs

Neutron Logs
  • Determines porosity by measuring the amount of hydrogen atoms (neutrons) in the pores.
  • Tool has a neutron source.
  • Hydrogen absorbs neutrons and emits Gamma rays.
  • Hydrogen is mostly found in formation fluids like water or hydrocarbons.
  • Can be run in Cased holes.
Neutron Curve
  • Measures effect of bombarding a formation with a strong source of neutrons. This bombardment upsets the radioactive equilibrium of the rocks in the bore hole and induces a secondary gamma ray intensity many times greater than the natural gamma ray radiation from these rocks.
  • Generally appears similar to resistivity curve of electrical log. Different neutron values due to presence of fluid will alter this similarity somewhat.
  • Does not represent lithology.
  • Is difficult to interpret alone.
  • Cannot be always correlated because it represents primarily fluid content.
  • Shale is normally the lowest curve value. This is due to the presence of hydrogen in the shale that slows the fast neutrons and reduces the incidence of capture, with resulting low secondary gamma ray radiation.
  • Shales may be used as a base line for curve.
  • Is not generally affected by highly radioactive formations.
Tool Operation:
  • The tool operates by bombarding the formation with high energy neutrons. These neutrons undergo scattering in the formation, losing energy and producing high energy gamma rays. The scattering reactions occur most efficiently with hydrogen atoms. The resulting low energy neutrons or gamma rays can be detected, and their count rate is related to the amount of hydrogen atoms in the formation.
  • In formations with a large amount of hydrogen atoms, the neutrons are slowed down and absorbed very quickly and in a short distance. The count rate of slow neutrons or capture gamma rays is low in the tool. Hence, the count rate will be low in high porosity rocks.
  • In formations with a small amount of hydrogen atoms, the neutrons are slowed down and absorbed more slowly and travel further through the rock before being absorbed. The count rate of slow neutrons or capture gamma rays in the tool is therefore higher. Hence, the count rate will be higher in low porosity rocks.
  • There are mainly three types of neutron tool, which are:
    • The Gamma Ray/Neutron Tool (GNT)
    • The Sidewall Neutron Porosity Tool (SNP)
    • The Compensated Neutron Log (CNL)
Typical neutron log responses in common lithologies
Typical neutron log responses in common lithologies
Density or Porosity Logs
  • Determines porosity by measuring electron density.
  • Dense formation absorbs more gamma rays while low-density formations absorb fewer.
  • High court rate at detector means low-density formation.
  • Mineral identification.
  • Gas detection (used in combination with neutron log).
  • Shale gas evaluations.
  • Delineate thin beds.
  • The formation density is a porosity log that measures electron density of a formation.
  • The gamma rays enter the formation and undergo compton scattering by interaction with the electrons in the atoms composing the formation.
  • Compton scattering reduces the energy of the gamma rays in a step-wise manner, and scatters the gamma rays in all directions.
  • When the energy of the gamma rays is less than 0.5 MeV they may undergo photo-electric absorption by interaction with the atomic electrons.
  • The flux of gamma rays that reach each of the two detectors is therefore attenuated by the formation, and the amount of attenuation is dependent upon the density of electrons in the formation.
  • Dense formations absorb many gamma rays, while low-density formations absorb fewer. Thus, high-count rates at the detectors indicate low-density formations, whereas low count rates at the detectors indicate high-density formations.
  • Therefore, scattered gamma rays reaching the detector is an inclination of formations density.
  • Scale and units: The most frequently used scales are a range of 2.0 to 3.0 gm/cc or 1.95 to 2.95 gm/cc across two tracks.
The tool consists of:
  • A radioactive source: This is usually caesium-137 or cobalt-60, and emits gamma rays of medium energy (in the range 0.2 – 2 MeV). For example, caesium-137 emits gamma rays with a energy of 0.662 MeV.
  • A short range detector. This detector is very similar to the detectors used in the natural gamma ray tools, and is placed 7 inches from the source.
  • A long range detector. This detector is identical to the short range detector, and is placed 16 inches from the source.
Schematic diagram of a formation density tool.
Schematic diagram of a formation density tool.

Gamma Ray Log

  • Measures radioactivity to determine the kind of rocks.
  • Decay of radioactive elements produces high energy gamma ray.
  • This gamma radiation originates from potassium-40 and the isotopes of the Uranium-Radium and Thorium series.
  • Once the gamma rays are emitted from an isotope in the formation, they progressively reduce in energy as the result of collisions with other atoms in the rock (compton scattering).
  • Compton scattering occurs until the gamma ray is of such a low energy that it is completely absorbed by the formation.
  • Hence, the gamma ray intensity that the log measures is a function of:
    • The initial intensity of gamma ray emission, which is a property of the elemental composition of the rock.
    • The amount of compton scattering that the gamma rays encounter, which is related to the distance between the gamma emission and the detector and the density of the intervening material.
    • The tool therefore has a limited depth of investigation.
  • Shale show high radioactivity as radioactive elements are concentrated in Shale
  • Sandstone and carbonate usually show low radioactivity.
  • Can be run in both open and cased hole.

Gamma Ray Curve
  • Measure the natural gamma ray radiation from the formation. No electrical properties are measured.
  • Generally appears similar to self potential curve of the electrical log.
  • Formations generally have a characteristic curve response according to type.
  • Can be readily interpreted alone in most areas.
  • Can be readily correlated with other information pertaining to the formation type.
  • Shale is normally the highest curve value.
  • No base line or zero. All recordings are positive.
  • Is greatly affected by highly radioactive formations.
  • Is not affected by changes in borehole diameter.
  • Id not affected by borehole and formations fluid.
  • Does not represent porosity or permeability.
Gamma Ray Spectral Log Presentation.
Gamma Ray Spectral Log Presentation.

3.4. Other Logs

NMR (Nuclear Magnetic Resonance) Logs
  • Measures magnetic response of fluids.
  • Measures both porosity and permeability.
  • Help determining the type of fluid in pore spaces.
  • Identify low-resistivity pay within water volumes.
Dipmeter Logs
  • Determines orientations of sandstone and shale beds.
  • Determines orientations of faults and fractures.
  • Measures resistivity of rocks.
  • Make detailed image of the rock around the well hole.
Image Logs
  • High resolution images of the borehole.
  • Electrical micro imaging technique.
  • Used to identify a variety of geological attributes like structural dip, faults and fractures.
  • Insight to the condition of the borehole, stress and rock mechanics around the borehole.
  • Helps in porosity determination.
  • Recent developments in LWD made it possible to acquire high resolution electrical borehole images. In real time these images can help to steer the drill bit.
  • Applications:
    • Detailed stratigraphic and sedimentological analysis.
    • This bed delination.
    • Fault mapping and structural analysis.
Caliper Logs
  • Measure the diameter and shape of a borehole.
  • Indicator of good permeability and porosity zones.
  • Calculation of mudcake thickness.
  • Measurement of borehole volume.
Typical caliper responses to various lithologies.
Typical caliper responses to various lithologies.

Wednesday, 23 April 2014



satellite image sikhar

The field excursion was done along the stream originating from the shikhar fall which has the geological location around Krol region. This Krol region which has got the various formations such as Mahi formation (krol A) , Jarashi formation (Lower member, Upper member and Lower member (Krol C)),and Kauriyala formation (Middle member(Krol D), Upper Member (Krol E)). Below to this Krol formation Infra Krol Formation is lying which is also called Blaini Formation.
This stream originating at the Shikhar fall flows though this Krol region and BalianAa region.
Following are features of this Shikhar fall: - 
The geological setting around the stream is forming the Musshorie Syn-cline.
Main Boundary Thrust (MBT), separates Lesser Himalaya (Jaunsar Group) from Sub – Himalaya (Siwalik Group).
Latitude of the place:
Longitude of the  place:
Types of the rocks found: Sandstone, shale, Slate,Quarzite, Limestone.
Dip direction: -15NNE SSW
Dip amount : - 36 degree


big boulders
Fig1: - Geological carrying of the big boulders down the stream 

In the due course of time the water force has brought down these bigger boulders down the channel and because of the slope difference it is being taken down and down. Because of collision and abrasion these big boulders will diminish in size and break into smaller pieces such cobbles, pebbles and gravels.


Fig 2:- Breccia


quartz veins
Fig 3 : - Primary and Secondary Calcite veins

This picture has got the calcite veins shown in white colour The calcite  veins are cross cutting each other in this picture. Also, the joints are clearly shown where one rock mass is lying over other


erosion of rock
Fig 4: - Showing erosion of the rock mass because of the hardness difference

The erosivility of the  rock surface is the function of hardness. The more harder the surface the less erosive it will be. In the above picture it depicts the same.


weathered rock mass
Fig5: Weathered rock mass because of the action of water and air


                                  Fig 6:-  Parallel rock blocks stacked together showing joints


Natural levees
Fig 7 :-  Natural levees formed showing the flow directions. 

The flow direction is determined from this clay cutting andthis is very important to understand the seasonal nature variation of the stream.


When we travel along the stream and many characteristic features of river keep on changing such as gravel size and roundness. With distance the gravel size keep on diminishing and degree of roundness keep on increasing . In other wordwe can say that the degree of roundness tells about the distance travelled by the rock sample.
Also, the stream keep on changing their flow direction with the level of resistance they encounter in their path. The current flow direction and paleodirection of the current can be studied from the flow marks seen on the levee structures and the rock samples.

Tuesday, 15 April 2014

Direct Hydrocarbon Indicators

Seismic Methods & Hydrocarbon Detection

Explorationists have long dreamed of a device or technique that they could use at the earth's surface to get direct indications of deeply buried hydrocarbons. Over the years, scientists, inventors, entrepreneurs -- and not a few eccentrics -- have used tools ranging from divining rods to gas sniffers to "black boxes" in pursuit of this dream. They've analyzed soil samples, studied vegetation and taken pictures of the earth. They've walked, driven, flown and even sent up satellites. But their efforts have generally gone unrewarded. True, there are documented cases where hydrocarbons at depth have been successfully measured at the surface. But in these cases, some of the hydrocarbons leaked to the surface along fault planes and were detected by geochemistry or geobotany analyses. The ultimate tool still alludes us.
The only "reliable" tool we have for measuring the subsurface at a satisfactory density is the seismic method. So let's see if and how we can use the seismic method as a direct hydrocarbon indicator.
With ever-increasing resolution and clarity, seismic exploration technology is moving beyond the role of simply imaging the subsurface. We can now discern patterns in a processed seismic section that tell us much about a structure's nature and geometry. This is well-documented in the classic AAPG Memoir 26, Seismic Stratigraphy (Payton, 1977) and more recently, in AAPG Memoir 42, Interpretation of 3-Dimensional Seismic Data (Brown, 1991). The logical next step, of course, would be for a seismic-derived image to be presented directly -- not only in terms of geometry, but in terms of lithology, fluid content and other parameters which bear on reservoir potential.
The Encyclopedic Dictionary of Exploration Geophysics defines a direct hydrocarbon indicator as "a seismic measurement which indicates the presence of hydrocarbon accumulation" (Sheriff, 1973). These measurements may be in the form of "bright spots", "dim-outs", flat spots, polarity reversals, velocity sags, frequency changes, increases of amplitude with offset and P- versus S-wave ratios, among others. We commonly abbreviate "direct hydrocarbon indicator" as DHI or HCI.

Seismic Problems

In identifying a potential reservoir, we need to define such parameters as
  • geographic location
  • shape, thickness and depth
  • rock type
  • porosity
  • permeability
  • type of pore fluid
Seismic data can help us determine these parameters in anticipation of the drill bit, but only when we have other, more direct subsurface information (i.e., well data). Thus, we must begin to systematically build information bridges, by which seismic data will provide the answers it promises. Wellbore-to-seismic correlations and geoseismic modeling are among the primary tools for such syntheses.
Industry pundits unanimously agree that "advanced seismic technology" is essential for profitability and even for survival in the face of relatively unpredictable oil and gas prices. Unfortunately, the marketing and presentation of seismic products and services offers a bewildering variety of recently developed processes, procedures and practices, including AVO, DMO, VSP, 3-D, 2 1/2-D, turning waves, multi-component, shear waves, inversion, tomography, and so on.
Of these processes, it is clear that DMO processing and 3-D seismic data have attained to the status of routine or nearly routine technology. Others are still considered research or quasi-research tools. But it is not clear how any one such piece of technology relates to any otherÉnor what it is intended to provideÉnor where the whole ensemble is going.
In addressing this topic, we need to single out practical and currently advanced seismic technologies that can be of benefit in finding and defining hydrocarbon reservoirs. The first step is to identify and examine seismic responses that may be related to the presence of hydrocarbons. We know these as bright spots, flat spots, dim spots, time sags, velocity slow-downs, amplitude variations and so on.
At present, there are two mainstream applications of seismic methods:
  • finding new reservoirs
  • better defining known reservoirs, and working out and away from them
The latter category of methods is the more recently developed one, and has given rise to the term development geophysics, which is to be distinguished from the former (and more familiar) category of exploration geophysics. Both applications draw on the same seismic technology, although they do so in different ways.
From our approach to seismic technology, it is likely that new reservoirs will be found and defined principally because we are now able to solve key seismic technical problems. Hence, discussions of seismic developments should relate to such problems and the nature of the reservoirs which have been overlooked. At the same time, we should look more closely at what seismic methods might teach us about such reservoirs and their properties both now and in the future.

Historical Perspective

Anyone involved with seismic technology -- whether in acquisition, processing, interpretation, or merely as an investor; and whether this involvement has lasted for two years, or twenty years -- has seen many changes in seismic technology. It has certainly not been a static technology; instead, it is overwhelmingly dynamic. In fact, it will "leave you in the dust" if you don't keep up with it.
Let's look at some recent developments in seismic technology as they relate to direct hydrocarbon indicators.
1960s and 1970s: the new geophysicist
In the late 1960s, the seismic method began to feel the impact of the computer revolution. There were dramatic changes in acquisition methods; seismic data processing developed; and common depth point (CDP) technology was born (Mayne, 1962). The late sixties also saw the birth of the seismic specialist. Where previously, the geophysicist stayed out in the field and was responsible for the total product from acquisition through interpretation (we affectionately know him as a "doodlebugger"), the "new geophysicist" specialized in acquisition...or processing...or interpretation. From this time on, only the acquisition expert went out to the field; the processor stayed at the computer center, and the interpreter stayed in the office.
In 1973, Tucker and Yorston released their classic work Pitfalls of Seismic Interpretation. This pamphlet presented twenty-three examples describing a series of problems that an unwary seismic interpreter might encounter to great regret. While the specific seismic data quality for the illustrations left something to be desired, the messages were clear. The pamphlet presented guidelines both for understanding each of the effects and further making a correct interpretation. Of special interest was the fact that all the interpretive difficulties were placed into just three categories:
  • · velocity
  • · geometry
  • · recording and processing
This pamphlet places the responsibility for addressing these pitfalls squarely on the interpreter, based on his or her skills, experience and intellect -- it offers few "crutches" beyond doing careful work and gaining as much experience as possible.
It is interesting that only three years later, Neidell expressed a somewhat different interpretive philosophy, which the AAPG later documented in a set of published course notes (Neidell, 1984). Based on this work, we can set forth an interpretation procedure for handling seismic data that begins with a processed seismic section. For the moment, we will suspend all questions or doubts about the effectiveness of the data processing, and interpret the section based on the following assumptions:
  • · Each trace of the section represents only primary reflections from the subsurface, having locations immediately below where we have shown them to be plotted.
  • · Individual reflection events can be identified, and their amplitude is diagnostic of the change in acoustic impedance across the boundary causing the reflection.
In this ideal world, we may simply state the objectives and procedures of both seismic and stratigraphic interpretation. Figure 1(relationship between lithology, propogating wavelet and seismic response) shows a portion of a lithology log and a corresponding acoustic impedance log.
Figure 1
Figure 1
Each contrast in acoustic impedance is marked by a reflection event having a simple waveform. The polarity or sense of the reflection and its size indicate the nature of the contrast. Individual reflection events for the model are shown, along with their summation in the resulting seismic trace.
Interpretation begins, then, with the development from each trace of an acoustic impedance log or, equivalently, a reflectivity series. We correlate these results trace-to-trace to provide the structural considerations, and correlate them also with whatever geologic information is available. Using geological principles and insights appropriate to the region, we infer lithologic estimates, and from these estimates and the indicated trace-to-trace changes, geometry and depositional patterns, we interpret sequences and history.
The question of the wavelet's shape is worth considering, as Figure 2 demonstrates.
Figure 2
Figure 2
As we can see, the same sequence of lithology viewed as an ideal normal incidence synthesized seismic trace is extraordinarily difficult to interpret on the basis of untreated waveforms.
Motivation for this approach followed from new developments in estimating seismic waveforms and converting them effectively to the simple zero-phase symmetric form shown in Figure 3 .
Figure 3
Figure 3
The individual superimposed waveforms are also shown to provide some reasonable perspective for understanding the superposition.
As with many significant developments, the control of seismic wavelets only represented one added element in the extraction of subsurface information from seismic data. In fact, during that same period, the role of seismic modeling as a quantitative bridge to subsurface parameters, and the use of seismic patterns for discerning lithology, depositional setting and other stratigraphic components was introduced in systematized form by Vail and the Exxon school of seismic stratigraphers (1977). In Figure 4, regional geology and borehole measurements are presented in relation to their expression as patterns which may be seen in the seismic view.
Figure 4
Figure 4
In the 1970s, we learned that (1) the pitfalls which might be encountered might have analytic treatments via seismic data processing or special field practices, and (2) that more information might be recoverable from seismic data than previously appreciated. The use of seismic patterns for interpretive purposes and the lessons from seismic modeling testified for the second goal.
As noted earlier, a respect for the information contained in the seismic response evolved. When particularly learned, the value of seismic amplitude and that retention of accurate amplitude information is a must. Rather than arbitrarily increasing the amplitude to maximize the structural content, we learned that maintaining "true" amplitudes (also called "relative" amplitude processing or RAP) could tell us much about certain qualities of the subsurface. And we found that when we did this, we noticed anomalously high amplitudes, or "bright spots," that we equated to qualities of oil and/or gas.

1980s - A critique

In the 1970s, we noticed the importance of bright spots and built a well-defined link between seismic interpretation and the role of data processing (and, to a lesser extent, acquisition). The 1980s saw increased efforts to perfect seismic imaging and extract as much subsurface information as possible. It became clear, for instance, that in an appropriate geologic setting, a porous, gas-filled Pleistocene or Pliocene sand on a properly processed and imaged seismic section would be readily recognizable. For example, we can identify an offshore Gulf Coast sand in Figure 5 .
Figure 5
Figure 5
The prominent trough denoting the sand top is labeled as is the gas-water contact and indicated by the essentially flat sequence of strong peaks.
For this same data, Dedman, Lindsey and Schramm (1975) interpreted most of the sands in the subsurface column between 1.0 and 1.8 seconds. Similarly, sands were identified by means of well log measurements, and plotted on a two-way travel time scale for direct comparison with the seismic data. The results are shown in Figure 6 .
Figure 6
Figure 6
In assessing the remarkable agreement, it is important to note that the top of a sand corresponds in each case to a trough, negative amplitude or "white event", while the base is defined by a peak, positive amplitude or "black event."
Hence, the waveforms inherent in our seismic data are more amenable to interpretation once we manipulate and transform them to simpler waveforms. We can now accomplish these transformations, in principle, for all reflection seismic data, and attain correlations between seismic data and geological inputs to produce more definitive results.
Figure 7 demonstrates the improved correlations of seismic images with subsurface data, this time using an elementary model, the synthetic seismogram.
Figure 7
Figure 7
A seismic section over a North Sea oil field has been separated at the well location, and several repetitions of the synthetic seismic signature computed from the velocity and density logs have been inserted. A common waveform is used in the actual processed data and the synthetic traces. Such agreements clearly enable correlations to be made which enable one to work away from the well control with a good degree of confidence.
Let's now look at a processed seismic section from the offshore Texas Miocene ( Figure 8).
Figure 8
Figure 8
In this case, the Miocene sands are associated with peak reflections, as distinct from the previous association of reflections from sands as troughs. The fact that sand reflections may be signaled by both peaks or troughs is rarely mentioned in the literature describing seismic technology (Rutherford and Williams (1989), Neidell and Berry (1989), and Neidell and Lefler (1992)). It certainly was not mentioned at all prior to 1989. Obviously, such a fundamental matter deserves to play a role in our thinking relating to seismic data, since some 50 percent of global hydrocarbon production relates to sands and sandstones.
The prominent GulfCoast gas sand of Figure 5 could also have been confirmed via seismic modeling as a companion to the log correlations performed by Dedman et al (1975), which were also previously shown in Figure 6 . For such a study, we could apply two-dimensional seismic modeling.
In Figure 9(synthetic seismograms developing a two-dimensional model of partially gas gilled sand anticline - band pass zero phase symmetric wavelet versus actual contractor wavelets A and B),
Figure 9
Figure 9
the model shows a mildly structurally closed sand unit of relatively uniform thickness. The upper 60 ft [18 m] of this 120 ft [36 m] sand is gas-saturated. Field seismic data exhibited a "bright spot" about the amplitude relief shown in the figure. This model was originally computed with theoretically derived rock velocities and densities for the sand and shale values from data calibrated to nearby well logs. An amplitude increase of only 25% was obtained using these values, and the model was altered to have the values shown in the figure. These were derived by assigning a .04 reflection coefficient to the shale-water sand interface and adjusting the gas sand velocity to provide the amplitude increase shown on seismic data. Densities were included in the reflection calculation and generally follow Gardner's equation. For a detailed discussion of Gardner's investigations, refer to Carter and Siraki (1993).
First, we computed model responses for two different but documented marine basic wavelets. These might be thought of as coming from two different contractors. It is not our position to choose between these two wavelets. It is apparent that the seismic sections look quite different, and if they were members of a grid of data on the same prospect, it would be difficult to tie them.
For conventionally processed data, it is generally unreliable to attempt picking the top and bottom of the gas-sand for thickness estimates. However, it would be possible to detect the probable presence of the sand and to place it on the map. Wavelet B might leave us wondering if we have one sand or two, while wavelet A causes us to wish for some higher frequencies in the hopes more detail as to the exact stratigraphy could be seen.
Both wavelets A and B have a bandwidth approximately equal to the 8-32 Hz response shown in the figure. Thus, this model response is what each of the other two could have been converted to, with appropriate processing. No problems of tying data between the two data sets would then exist.
We should in fact have become quite suspect at this point, in that even this simple application of modeling required us to force parameter values to achieve an acceptable fit. Strictly speaking, our model should also have included multiples, as the North Sea synthetic seismogram should have ( Figure 7 ). Experience has taught us that including all multiples in model calculations (of any type) degrades our fits substantially, although from time to time we can document the presence of a multiple or two.
Unfortunately, our quest for added information from seismic data forced us to face circumstances in which the available tools could not solve the problem. Figure 10and Figure 11 clearly illustrate this point.
Figure 10
Figure 10
These figures were developed from the Rocky Mountain area, and exemplify the problem of distinguishing between a coal seam and a partially gas-filled sand encased in a sandy shale.
Figure 11
Figure 11
Simulated time sections (with and without noise, using a fairly typical bandwidth) suggest that in practical terms, it is not likely that this distinction could be reliably accomplished using normal seismic displays and techniques.
The 1980s saw the introduction of new forms of HCIs. In the early eighties, seismic inversions became a popular means of directly identifying subsurface hydrocarbons. In this method, the seismic trace is converted to a synthetic impedance well log. When we apply inversion to a series of adjacent seismic traces, we then produce a synthetic impedance section. We interpret the impedance section as if we had a series of closely spaced acoustic, or sonic well logs.
The late 1980s also saw the use of amplitude data develop as an alternative. Using equations of energy partitioning, we began relating changes in amplitude as a function of distance from source to receiver (or offset) to changes in fluid type. Depending on the circumstances, we observed that seismic amplitudes either increase or decrease according to the fluid content. This type of HCI is called amplitude versus offset, or simply AVO. Using this method, the problems of discrimination shown in Figure 10 and Figure 11 could possibly be resolved.

View of the 1990s and beyond: the 3-D explosion

We may now consider making "ties" between seismic data and the subsurface as we know it from wellbore observations and measurements. There are many aspects to such an objective. One obvious one is the initial issue of imaging seismic data most effectively. We must also examine how we may best use such displays. Currently, we are experiencing an explosion in seismic technology in the form of 3-D data. This new technology, along with advances in computer workstations, is forcing us to learn new ways to operate, process and interpret seismic information. It is important to clearly appreciate the relationship of 3-D technology to 2-D methods. Fortunately, this is a simple matter, and involves only a straightforward extension of 2-D technology.
At the same time, we must clearly define (even on a global basis) the geological relationships between lithology and their characteristic reflections. Also, we must carefully scrutinize the models we employ and the theoretical equations on which we rely. We have already seen major discrepancies between such models and the behavior they predict (for example the prediction of the presence or absence of multiple reflections and the ability to predict seismic amplitude levels). If there is to be real progress, we cannot tolerate blind spots of such basic importance.
Just as the early 1990s brought us to new high resolution in the horizontal domain in the form of 3-D seismic, we will see new revolutions in the vertical domain in the late 1990s. At that time, no longer will a 2 ms sample rate and 20 ft resolution be the norm, but we will routinely see 0.1 ms data and 1 ft vertical resolution.

Monday, 14 April 2014

Geological Field Report - Vindhyan System


Field Site: Son Valley, Upper Vindhyan Basin, Madhya Pradesh.

Local Geology: The Son Valley comprised of Vindhyan Formations like Semri, Rewa, Bhander etc. of varying lithology comprising shale, sandstone and limestone.

Description: The Vindhyan System derives its name from the Vindhya Mountains,a part of which is found to form the prominent plateau like range of sandstones to the north of the Narmada valley, particularly in Bundelkhand and Malwa. It occupies a large basin extending from Dehri-on-Sone to Hoshangabad and from Chittorgarh to Agra and Gwalior, surrounding the Batholithic mass of Bundelkhand granite. Over the greater part of the area, only the upper portion of the Vindhyans is developed, usually resting on the Cuddapahs. This report presents understanding the formation of the prominently visible sedimentary structures in the basin.
The Vindhyans consist of four main series namely:
1.Bhander Series:
Mostly contains Arenaceous and calcareous types of rocks with a average thickness of 450 meters

2.Rewa Series:
Mainly consists of arenaceous types of rocks with a thickness ranging in between 150-300 meters

3.Kaimur Series:
Mainly consists of arenaceous types of rocks with a thickness ranging in between 150-300 meters

4.Semri Series:
Mainly consists of calcareous types of rocks with a thickness ranging in between 300-900 meters

Day 1

January 8th 2014
SPOT 1Behind Maihar Temple
Coordinates:240 16’54.5’’N 80042’42”E
  • The formations present here are under the Upper Bhander Group, the uppermost division of the Vindhyan basin.
  • The layer coarsens upwards.
  • Upper Bhander comprises of Shikoda Sandstone and Shirbu Shale.
  • Shirbu shale is present at the bottom of the hill.
  • Sandstone present is usually hard and thick.
  • Basically red colour laterite soil is present.
  • Vegetation prevalent due to presence of Potassium.
  • Charniodiscus: A fossil found in the region indicating Precambrian and Cambrian border.

Cross Lamination

SPOT 2: Lower Bhander Formation
Coordinates: 240 16’54.5’’N 80042’42”E
  • Formations present here are under Upper Bhander Group.
  • Age of formations is approximately about 570 million years (Neo Proterozoic).
  • Both red and white sandstones are found.
  • Red Sandstone More iron content
  • White Sandstone More silica content
  • Ripple marks present indicates turbulence during deposition time.
  • Other structures found are:
    • Cuspate ripples (formed in high flow regimes).
    • Dessication cracks (has fine mineralogy).
  • Black shale (Shirbu shale) are source rock of this place
  • Some characteristics of Shirbu Shale are:
    • They are generally khaki or grey colored.
    • These are black shale due to presence of organic matter.
  • Due to thermal alteration processes there are various changes that happen over to the rocks. Predominantly their colour changes, as the list shows below:
    • Light Brown Colour - Diagenesis
    • Blackish Colour - Catagenesis
    • Black Colour - Metagenesis
  • Fossils found of age varying between late Pre-Cambrian to early Cambrian are present.
  • Macrofossils assemblages Chuaria-Tawuia are found only in one particular layer in matty structures.
  • Fossils only in linear beddings. No fossils found in cross beddings.
  • Presence of Architarch: Small organic fossils (indicates Cambrian age).

Ripple Marks

Alternate layers of sandstone and siltstone

Day 2

(January 9th 2014)
SPOT 3: Kuteshwar Limestone Mines
Coordinates: 23058’27”N 80050’67.7”E
  • KuteshwarLimestone Mine (SAIL):
    • Sides of this mine are covered by Kaimur Hills.
    • Asia’s longest limestone mine conveyor belt (approximately 11 km).
  • Limestone present here is Kajrahat Limestone.
  • Kajrahat Limestone (Semri Group*) -
    • Rich of organic matter
    • Calcitic Limestone ( calcite vein between limestone)
    • 1800 Myrs
    • Fan fabric structure – Radiating structure
    • Shallow Marine Environment
  • Bench Depth – 6 mts.
  • Loading site – Khanamajari
  • Kuteshwar mines had a proven reserve of 151.43 million MT of SMS gradelimestone.
  • By December 1992, the mine was equipped with 14 drills, 18 dumpers, five dozers, five excavator/front end loaders, one crane and onewater sprinkler valuing Rs. 9.92 crore.
  • The work was completed in August 1998 against scheduled completion date of November 1997.

Landscape view of Kuteshwar Mines

SPOT 4: Rewa Group
Coordinates: 2404.855’N 80049.363’E
  • Neo Proterozoic (Early)
  • Mainly consists of arenaceous types of rocks with a thickness ranging in between 150-300 meters
  • Three Sets are well defined under the Gilbert Depositionthat denote the flow directions:
    • Top Set
    • Fore Set
    • Bottom Set
Rain Prints
Rain Prints
SPOT 5: Girgita Bhander Limestone
  • Sedimentary Structures:
    • Molar Tooth – Bounded by limestone nodules.
    • Continuous bed of molar tooth structures is found only in neo Proterozoic.
Stromatolites: Organosedimentary structures are also found in abundance.

Sedimentary Structures

Molar Tooth Structure
Molar Tooth Structure

Day 3

(January 10th, 2014)
SPOT 6: Lower Bhander Limestone
Coordinates: 24043.544’N 8301.123’E
  • Formation: 510 Million yrs
  • Dolomite of pink color (due to the presence of Mg) is present.
  • Molar Tooth Structure
  • Stromatolites of different shapes are found.
  • Bhander Group is characterized by the dominance of Colonnellacolumnaris.(Shown in Fig. 14 (a) &(b))
  • The other five types of stromatolites reported from the bhander group which show active branching are Baicaliabaicalica, B. burra, Patomiaossica, Cryptozoon sp. andMaihariamaiharensis.
  • Presence of Edgewise Conglomerateand Ooliticchert (4-5 cm depth).
SPOT 7: Sajjanpur Lakher
  • Upper Bhander Limestone
  • MISS (Microbial Induced Sedimentary Structure):
    Made up of organic matter - Sandstone (Siliciclastic).
  • Stromatolites, Wrinkle Marks and Molar Tooth structures are found.
    • BaikaliaStromatolites
  • Algal Matt like structure – Impression of the cyanobacteria.
  • Matt is formed when there is no flow and sedimentation takes the shape.
  • Formation of Syneresis Cracks.
  • Chert nodules are formed where there is rapid flow.
  • Silica is pinched out – resistance to weathering whereas limestone weathers quickly.
Algal Matt
Algal Matt
Syneresis Crack
Syneresis Crack
Chert Nodules
Chert Nodules

Day 4

(January 11th, 2014)
Industry Name: Prism Cement
  • Lecture by Mr. B.P. Pandey(Mining Surveyor,Prism Cement)
  • Band thickness- Less
  • Wideness-2km
  • Including belts- Panna, Satna and northern side of Rewa.
  • Lithology of area:
  • The overburden has thickness upto 0-5m.
  • The upper shale limestone, or the waste rock, has a content of 34-38% of CaO.
  • The limestone is present in a larger area having intercalcareous layers. It has a thickness of 4-15m.
  • The lower shale limestone has thickness upto 3m.
  • Top soil is preserved.
  • Normal thickness of bench for blasting: 6m.
  • The overburden has the following layers:
    • Soil
    • Subsoil
    • Shale
    • Shaly Limestone
  • Sometimes, depending upon the situation, 2-3 benches are drilled through.
  • The Bhander series present in this region begins at Garaghota, Sagar district, Madhya Pradesh.
Landscape view of Prism Cement Mines
Landscape view of Prism Cement Mines
  • Different units and their specifications:
    • Unit I:
    • Hammer type (FLS) crusher
    • 1200 DPH.
    • Unit II:
    • Single Impact Rotor Crusher.
    • 750x2 DPH.
    • Manufacturer: L&T
  • Other than this, 4 waybridges are also installed to handle and capacitate the production from 20,000-25,000 tonnes of limestone and 25,000- 30,000 tonnes of overburden.
  • Pile formationhappens after crushing.
    • Size of grains: 75- 200mm
  • Noise and Fly Rock Control:
    • Devices:
      • NONEL of IDL
      • Conventional explosives from local market. (Base and Booster)
Beneficiation done through Portable Screen.
  • Steps involved for acquiring mines and setting up industry:
    • Permission from state government for mining lease.
    • Permission from Mineral Resource Division (Bhopal).
    • Acquiring land for industry setup from government.
    • Acquiring surface rights from collector.
    • Permission from Ministry of Environment.
    • Technical approvals.
  • Some characteristics features of the mines at Prism Industries are:
    • Fully mechanized captive mines.
    • Daily production is approximately 20000-25000 tonnes.
    • Limestone and overburden are present in 1:1 ratio.
  • Sequential steps in mining are:
    • Deephole drilling.
    • Blasting
    • Excavation
    • Transportation

Power Screens

Pile Formation and Transportation

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