Seismic Hydrocarbon Indicators

There are three types of hydrocarbon indicators in seismic:-

1.Bright spot

2.Dim spot

3.Flat spot

Bright spot: Bright spots are the high amplitude seismic anomaly that indicates presence of hydrocarbon.Bright spots primarily results due to increase in acoustic impedance contrast such as when a low impedance gas zone is overlain by high acoustic impedance shale thus increasing the reflection coefficient.Bright spots can also happen due to change in lithology.

Figure:- Acoustic impedance relation which leads to bright spot.

 https://commons.wikimedia.org/wiki/File:Seismic_bright_spot.svg

Dim spot:- Dim spot are low amplitude seismic anomaly that indicates presence of hydrocarbon,Dim spot result due to  reduction in acoustic impedance contrast  when hydrocarbon  zone  is overlain by low impedance  shale .

Similar to bright spot, dim spot can also happen due to lithology.

Acoustic impedance of sands and shales increase with age and depth but phenomenon is not uniform.Acoustic impedance of younger shales are higher than younger sands,but this reverses at higher depth with acoustic impedance of older shales higher lower than older sands. 

Figure:- Acoustic impedance relation which leads to bright spot.

https://commons.wikimedia.org/wiki/File:Seismic_dim_spot.png

 Flat spot: Flat spot represents a fluid contact ,They appear on seismic section as horizontal reflector. They are very prominent on seismic section as they are flat compared to surrounding dipping reflector.They can show downdip limit of reservoir in some cases.

Figure:-Flat spot in seismic section, 

From:-  https://upload.wikimedia.org/wikipedia/commons/7/75/Flat_Spot_in_Seismic.jpg

Above mentioned hydrocarbon indicators are mostly found in relatively young,unconsolidated siliciclastic sediments,as these sediments may have large acoustic impedance contrast,prominent examples are Offshore western Africa and Gulf of Mexico.One big problem with these hydrocarbon indicators is they cant differentiate between high gas saturation and low gas saturation (fizz water).

Petroleum & Petroleum system

 Petroleum

Petroleum is basically a mixture of some of the naturally occurring hydrocarbon compounds which are found in rock. It exists in solid, liquid and gaseous states in accordance with the surrounding pressure, temperature and composition. It could be with or without impurities like sulphur, oxygen and nitrogen and can have considerable differences in its physicochemical properties such as colour, gravity, odour, sulphur content and viscosity in petroleum from varied areas.

Petroleum System:

Petroleum System is a vast term which includes geologic components and processes significant for the generation as well as storage of hydrocarbons. It comprises of mature source rock, migration pathway, reservoir rock, trap and seal.

To accumulate and preserve hydrocarbons, suitable relative timing is required for the formation of these elements along with the processes of generation, migration and accumulation. In the basins or regions, where a complete petroleum system has certain likelihood of existence, exploration plays and prospects are developed considerably.

Source rock, trap, seal & reservoir rock are key elements of petroleum system.A petroleum system mainly incorporates an active source rock and all genetically related oil and gas accumulations. It further incorporates geologic elements and processes that are significant if there is oil and gas accumulation exists. The presence of Petroleum System must be identified before initiating the exploration.

Source Rock

It is a subsurface sedimentary rock usually shale or limestone, they have the ability of generating or already generated movable quantities of hydrocarbons.

A rock must have three major features to be a source rock:

1. Quantity of organic matter
2. Quality capable of yielding moveable hydrocarbons
3. Thermal maturity.

Source rocks are mainly categorised into three basic categories on the basis of kerogen they contain. They are described in the next table.

1.      Type1 source rocks:-Formed from algal remains deposited in oxygen depleted conditions in deep lakes.These source rocks when subjected to high thermal stress during deep burial produce waxy crude oil.

2.      Type 2 source rocks:-These type of source rock are produced by marine planktonic and bacterial remains preserved under oxygen depleted conditions. Type 2 source rock tend to produce both oil and gas when subjected to high pressure and temperature.

3.      Type 3 source rocks:-These type of source rocks are mainly formed by land plants that got decomposed by bacteria and fungus .They tend to generate mostly gas and some associated light oil.

Discussion will be continued in next blog.......

                   

Seismic Data processing in Geophysics

The main objective of Seismic data processing is to convert the field recorded data into a form through which geological information can be extracted.

The seismic data processing objectives can be stated as below:-

(1) Present the reflections on the record sections with the greatest possible resolution and clarity and the proper geometrical relationship to each other.

(2) Eliminate or at least suppress all noise ,noise here is defined as signals not associated with primary reflections/earths reflectivity series. Sometimes noise gets mixed up with primary reflection.Noise cannot be removed completely but the ratio of signal to the noise level needs to be increased.

(3) isolate reflections from ghosts & multiples and surface waves.

(4) Obtain subsurface information (velocities, reflectivity etc.)

(5) Obtain a realistic image by geometrical correction /migration.

First step before starting data processing is loading the data. Field geometry should be applied on the data; this geometry is mainly the location of shot points, receiver locations corresponding to the traces acquired. 

Seismic Data Formats: Almost every program and every large oil companies has developed their own format. In the Course of time several standards have also been developed, to make an exchange possible between the different programs. The most important standards are: SEG-Y ,SEG-D & SEG-2

SEG stays for Society of Exploration Geophysicists. This is the most important society of geophysicists and seismologists in the oil industry. The different formats are very similar. The most widely used standard today is the SEGY format. Every file consists of several parts. The standard describes which information is put where in the file:

The other Formats SEG-D and SEG-2 are often used for the storage of raw data. They are suitable for multiplex data and make it possible to save traces with different lengths. For example, the SEG2 format saves each shot separately. 

Seismic data processing starts with  Preprocessing of data  to extract maximum information from the existing data. The steps involved in this process are as follows:

Editing of Data: Data reduction and editing is done mainly in this step, bad Field file Identification Number , bad channels noisy channels, poorly planted geophones, channels contaminated by power line noise, etc are all removed. 

Stay with us to read more on basic seismic data processing….

Integration of Probabilistic Evaluation Technique with Thomas- Stieber model

Applying Probabilistic evaluation technique with Thomas- Stieber model for minimizing uncertainty in Laminar and dispersed shale distribution calculation.

 Thomas  Stieber model has been used as standard tool for evaluation of laminated sand shale sequence for long time, Model  is based on  total porosity vs Volume of shale  cross plot to identify laminated ,Dispersed and structural shale’s distribution. This study investigates the accuracy of Thomas Stieber model for evaluation of dispersed and laminated shale volumes. Objective of this study is to identify errors in estimations of dispersed and laminated shale volume owing to presence of different clay types in shale due to clay diagenesis. The study further proposes a workflow by integration of probabilistic evaluation with Thomas Stieber model for more robust estimation of dispersed and laminated shale volumes.

Workflow developed focuses on integrating Thomas Steiber technique with probabilistic formation evaluation. Workflow accounts for errors in input parameters of model and minimizes them using least square error optimization technique. Addition of Elemental capture spectroscopy data if available further increases accuracy of clay type evaluation. Once clay type evaluation is done, all different clay types are modelled separately for laminated, dispersed and structural clays using Thomas Stieber method. Next step in workflow is to integrate all separately modelled laminated, dispersed and structural clays to get accurate volumes of laminated, dispersed and structural shales. Uncertainty analysis of results is also performed to determine sources of error and recommendations to minimize them.

In case of sand and single clay shale’s, Thomas Stieber model can be used to estimate laminated and dispersed shale volume. However Clay diagenesis may results into multiple and mixed layer clays, resulting into poor estimation of sand fraction in laminations using Thomas Stieber model due to total porosity variations as a result of clay bound water variations. This creates uncertainty in anisotropy based formation evaluation resulting into error in estimation of laminated and dispersed shale distribution. Proposed workflow helps in reducing errors in shale distribution calculation due to variation in clay types within shale. Reduction in shale distribution error results into minimizing the uncertainty on sand resistivity and sand porosity estimation which leads to more robust water saturation estimation in laminated sands.

Integrated Formation Evaluation of Complex clastic reservoir in exploratory well

Complex clastic reservoirs need intergrated interpretation approach, In some of the world producing  clastic reservoir  like we observe in Vietnam’s Nam Con Son basin  where Upper part of this basin contains Miocene clastics; significant feature of these clastic reservoir  is the presence of high carbonate cement - coupled with high diagenesis in associated clay resulting into variable clay structure and clay electrical properties which leads to formation evaluation uncertainties. This abstract  presents a introduction of integrated interpretation in such complex clastic reservoirs  and recommends Best practices and emphasizes the deficiency of single sensor approach and value of an integrated approach.

   

 Thorough interpretation of complex clastic reservoir for maximized benefits needs systematic integrated approach with proper understanding of various sensor data. Sensors needed for Integrated interpretation of complex clastic reservoir are Core data , nuclear magnetic resonance, Elemental spectroscopy, Image, Acoustic and conventional sensors data for determination of reservoir behavior and creation of optimized exploration program. This work presents a development of  dynamic interpretation workflow  as per standard practices and  modified as per lessons learned during the project. Final workflow developed, helped to calculate accurate Reservoir properties and behavior.

 Complex clastic reservoirs poses challenge in determining matrix porosity; any error in identification of matrix property such as matrix density can lead to incorrect estimation of matrix porosity. Elemental spectroscopy data helps in determining matrix lithology, matrix density can be estimated once matrix lithology is known. Photoelectric factor is an important measurement for lithology identification but it was challenging to use it in this interpretation due to clay diagenesis resulting into variable mixing of different clay types. Complex lithology also results into high variation in reservoir quality especially relative permeability, clay, capillary and free fluid porosities.NMR enabled obtaining  permeability and porosity portioning in addition to qualifying fluid typing .. Variation of NMR porosity as compared with Elemental spectroscopy porosity also helps in identifying porosity variation due to hydrogen index effect even in low porosity complex reservoir. Finally obtained stoneley permeability from acoustic tool is calibrated with other permeability measurement and Flow zone index is estimated. Workflow developed helps to understand reservoir behavior and calculates important reservoir properties including Clay type, Clay volume, ClaySilt ratio, water saturation, porosities, permeability and Flow zone index with significant accuracy while also correlating with testing and sampling results.

This work establishes a workflow for use and integration of various available data to determine complex clastic reservoir behavior. Novelty of workflow lies in its dynamic nature, it starts as a standard workflow but its modified as newer information are obtained about reservoir and new lessons learned during interpretation phase.    

A Formation Evaluation Workflow using Multi-Detector Pulsed Neutron Tool for Evaluation of Low Salinity Reservoir

This study presents an workflow for formation evaluation that integrates a multidetector pulsed neutron measurement with neural network as an cost effective solution, as compared to conventional open hole formation evaluation. The integration workflow can be used to estimate the following reservoir properties to solve formation evaluation challenges: 1) cased hole total porosity, 2) mineralogy, 3) gas and oil saturation, 4) synthetic bulk density, 5) neutron porosity, and 6) deep resistivity.

In Gulf of Thailand operations, logging programs are controlled by economics. Because of the high compartmentalization of reservoirs, well life is relatively short, which decreases the return on investment associated with expensive rig time and low commodity prices. Logging-while-drilling (LWD) failures are common because the temperature in the zone of interest is often near the operational limits of the LWD sensors. The need for additional logging runs significantly increases the expensive rig time. The multi detector pulsed neutron tool provides a novel, gas sensitive measurement  and an oil sensitive measurement, the carbon/oxygen  ratio in inelastic mode. The integrated workflow that combines Gas sensitive measurement, carbon/oxygen ratio and neural network can solve formation evaluation challenges in low salinity reservoirs by performing hydrocarbon saturation estimation and fluid phase identification in the same time.

Formation evaluation using a sigma mode of the conventional two-detector pulsed-neutron tool does not provide proper gas saturation evaluation because formation water salinity values in the Gulf of Thailand range from 4 to 5 kppm in the reservoir section. The inelastic mode of the two-detector pulsed-neutron tool also fails to provide gas saturation measurements as a result of the low carbon density of gas. This result makes the two-detector pulsed-neutron tool completely blind to gas in the Gulf of Thailand reservoirs. The technology associated with multi detector pulsed-neutron tool provides a novel, deep gas sensitivity measurement.

The data obtained from the multidetector pulsed-neutron tool and associated workflow by integrating of neural network can be considered as an alternative and economical formation evaluation solution in low salinity reservoirs, especially in offshore platforms where expensive rig time dominates logging decisions, because this tool can be run in a cased hole in a rigless operation. 

This work presents a proposed workflow using a multidetector pulsed-neutron tool for formation evaluation to help operators to overcome the complexities associated with the management of their assets without compromising quality. The new saturation estimate technique addresses the challenge of a lack of knowledge about reservoir water salinity and overcomes the porosity and lithology dependency. The predicted triple-combo data using cased hole interpretation modeling will help operators to reduce expensive offshore rig time in the event of LWD failure.

Gulf of Thailand: Cased Hole Formation Evaluation Challenges

Meeting formation evaluation challenges in low salinity gas bearing reservoir of Gulf of Thailand using a new pulsed neutron technology with neural network  

In Gulf of Thailand operations, logging and formation evaluation programs are controlled by economics. Due to  highly compartmentalized reservoir , the well life is relatively short which decreases the return on investment especially with costly rig time. More complexities arise due to tool failures where temperature in the zone of interest is often close to LWD sensors operational limits. In case of tool failure, another logging run will increases the cost associated with rig time significantly, this sometimes, leads to minimizing or canceling the logging program which in turn complicates the reservoir petrophysical assessment due to not enough or low quality data.

The  new generation multi-detector Pulsed neutron tool , with its third detector provides

 1) deep reading gas response,

 2) additional deep sigma,

 3) near-long capture ratio, 

 4) near-long inelastic ratio and 

5) other gas indicators that can be used to detect gas behind tubing/casing.

In this abstract we present an innovative method  for formation evaluation of gas sands in highly compartmantalized reservoir in high temperature reservoir , the workflow proposes a model to calculate

1) cased hole total porosity using near-long capture ratio,

2) mineralogy using capture spectrum elemental yields, 

3) hydrocarbon (gas) saturation using a long detector gated ratio curve in a technique that doesn't require a prior knowledge of formation water salinity and 

4) a synthetic triple combo (density, neutron and resistivity) curves using neural network

The proposed new technology and formation evaluation workflow with neural network  modelling provides all needed information for decision making using single tool that can be run in rigless operation in cased hole to overcome the complexities associated with data acquisition while drilling and minimizing the risk of using chemical source type tools in challenging logging environment. Moreover it will help achieving an effective data acquisition cost without compromising the quality of formation evaluation