SEISMIC INVERSION: COMPARISON OF ACOUSTIC AND ELASTIC IMPEDANCE INVERSION MODELS FOR ROCK PROPERTY PREDICTION


SEISMIC INVERSION: COMPARISON OF ACOUSTIC AND ELASTIC IMPEDANCE INVERSION MODELS FOR ROCK PROPERTY PREDICTION

ABSTRACT

Niger Delta is one of the major hydrocarbon-producing basins in the world. This basin has a quite complex geology which makes routine seismic interpretation a challenging task for understanding the reservoir properties such as lithology and fluid content. Seismic inversion has proven to be a reliable tool for a detailed understanding of the reservoir, especially for lithological identification.

In this study, the effort was made to compare acoustic and elastic impedance volumes with regard to litho-fluid discrimination in an offshore field in the Niger Delta. For this purpose, five horizons were interpreted to determine geological inputs for the impedance model building. Well, log data was tied to a near post-stack seismic volume and this was used in creating an initial acoustic impedance model. Thereafter, an initial elastic impedance model was created using well log data tied to a far post-stack seismic volume. The initial elastic impedance model was created with an elastic impedance log generated at 360 which conforms to the incident angle for the far offset stack. Following analyses of the initial models at the well location, a full model-based acoustic and elastic impedance inversion were carried out separately for the entire area, using the interpreted horizons as controls.

The inverted results reveal reservoir tops and show lateral variations in lithology away from the well location. In particular, the elastic impedance inversion gave superior results only in areas where the acoustic impedance log used in inverting the near seismic volume is near-constant through top reservoir transition. In areas where the acoustic impedance log could clearly distinguish the reservoir top, the acoustic and elastic impedance volumes gave comparable results. In comparison to the individual input seismic volumes, the inverted results would greatly improve reservoir property interpretation with possible integration with seismic stratigraphy.

TABLE OF CONTENTS

CERTIFICATION ............................................................................................................................................... i

DEDICATION .................................................................................................................................................. ii

ACKNOWLEDGEMENT .................................................................................................................................. iii

ABSTRACT ..................................................................................................................................................... iv

TABLE OF CONTENTS ..................................................................................................................................... v

LIST OF FIGURES .......................................................................................................................................... vii

CHAPTER ONE ............................................................................................................................................... 1

INTRODUCTION ......................................................................................................................................... 1

  1.1 BACKGROUND OF STUDY .......................................................................................................... 1

  1.2 STATEMENT OF PROBLEM ........................................................................................................ 3

  1.3 OBJECTIVE OF THE STUDY ......................................................................................................... 5

  1.4 SIGNIFICANCE OF THE STUDY ................................................................................................... 5

  1.5 SCOPE OF STUDY / LIMITATION ................................................................................................ 6

  1.6 STUDY AREA .............................................................................................................................. 7

CHAPTER TWO .............................................................................................................................................. 9

LITERATURE REVIEW ................................................................................................................................. 9

  2.1 THEORETICAL/CONCEPTUAL FRAMEWORK .............................................................................. 9

  2.2 REVIEW OF IMPEDANCE INVERSION METHODS ..................................................................... 16

      a) Band Limited (Recursive & Advance recursive)| .................................................................... 17

      b) Blocky (or Model-based) Inversion ......................................................................................... 19

      c) Sparse spike inversion ............................................................................................................. 19

      d) Neural Network Inversion ....................................................................................................... 20

      e) Geostatistical Inversion ......................................................................................................... 20

  2.3 REVIEW OF PREVIOUS WORKS ................................................................................................ 20

  2.4 GEOLOGY OF THE NIGER DELTA .............................................................................................. 22

CHAPTER THREE .......................................................................................................................................... 26

  METHODOLOGY (IMPEDANCE INVERSION) ............................................................................................ 26

  3.1 RESEARCH DESIGN .................................................................................................................. 26

  3.2 NATURE OF DATA / SOURCES OF DATA .................................................................................. 26

  3.3 METHODS OF DATA ANALYSIS ................................................................................................ 27

    3.3.1 Data Loading ................................................................................................................... 27

    3.3.2 Data Transformation ....................................................................................................... 29

    3.3.3 Well to Seismic Tie .......................................................................................................... 31

    3.3.4 Initial model .................................................................................................................... 35

    3.3.5 Analysis of the Initial Model............................................................................................ 36

    3.3.6 Inversion .......................................................................................................................... 36

CHAPTER FOUR ........................................................................................................................................... 37

RESULTS AND DISCUSSION...................................................................................................................... 37

  4.1 PRESENTATION OF DATA ........................................................................................................ 37

  4.3 DISCUSSION OF FINDINGS ....................................................................................................... 43

CHAPTER FIVE ............................................................................................................................................. 44

  CONCLUSION AND RECOMMENDATION ................................................................................................ 44

  5.1 CONCLUSION ........................................................................................................................... 44

  5.2 RECOMMENDATION ............................................................................................................... 44

REFERENCES ................................................................................................................................................ 46

CHAPTER ONE

                                    INTRODUCTION

1.1 BACKGROUND OF STUDY

The development of structurally composite oil and gas fields requires a careful understanding of

reservoir characterization so as to make the field performance more efficient.  This  requires

combined scrutiny and understanding of the existing data such as seismic data and well log data.  

Seismic data make available vital information about the common geology of the area. However,

extracting geological information such as porosity, density, and shale volume is a great challenge

for an interpreter. In seismic studies, seismic inversion is one of the great tools used in estimating

detailed properties of the reservoir rock. Inversion is the process of extracting, from seismic data,

the underlying geology which gave rise to that seismic (Hampson Russell).  

The basic objective of seismic inversion is to transform seismic reflection data into a quantitative

rock property, descriptive of the reservoir (Ogagarue, 2016). Conventionally, inversion has been

applied  to  post-stack  seismic  data due  to  their  ready  availability with  the  aim  of  extracting

acoustic impedance. In recent times, inversion has been extended to pre-stack seismic data, with

the aim of extracting both acoustic and shear impedance.  This  allows  the  calculation  of  pore

fluids.

During the last decades, several methods for estimating rock properties from seismic data were

introduced and tested with  the objective of providing further information for detailed reservoir

characterization. The first deterministic inversion methods for acoustic impedance mapping were

developed in the late 1970s and became known generally as recursive inversion (Lavergne and

Willem, 1977; Lindseth, 1979). 

Nowadays,  most  of  the  research  efforts  in  this  field  are  focused on the  inversion  and

interpretation  of  variations  of  seismic  reflection  amplitude  with  change  in  distance  between

source and receiver (amplitude vs. offset) from pre-stack data. Because wells in a reservoir field

are  often spaced  at  hundreds  or  even  thousands  of  meters,  the  ultimate  goal  of  a  seismic

inversion procedure in the context of reservoir characterization is to provide models not only of

acoustic impedance but also of other relevant physical properties, such as effective porosity and

water saturation,  for the inter-well regions.  Such  quantitative  interpretations  may  sometimes

require  the  use  of  other  seismic  attributes  in  addition  to  the  traditional  seismic  reflection

amplitudes  (Rijks  and  Jauffred,  1991;  Lefeuvre  et al.,  1995;  Russell,  2004;  Sancevero  et  al.,

2005; Soubotcheva, 2006).

Diverse seismic inversion methods are viably used to map detailed reservoir rock properties such

as lithology  and  fluid  properties.  These  properties  are  estimated  by  using  different  inversion

algorithms  on  the  seismic  data  with erstwhile geological  knowledge  and  well  log  data.  The

relationship  between  seismic  and  lithology  is  empirical.  The  reduction  of  uncertainty  in  this

relationship  will  have  large  effect  on  the  reservoir  model  building,  thus  on  development  and

production of the hydrocarbon (Badri et al., 2002). The inverted impedance model is also used

for  building  facies  and  facies-based  porosity  and  permeability  model  (Shrestha  et  al.,

2002).Seismic characteristics obtained from  time,  amplitude  and  frequency  do  not make

available satisfactory information of reservoir properties on a layer by layer basis. Layer by layer

information  can  be  derived  by  means  of  stratigraphic  inversion  of  post  stack  seismic  data  in

terms of acoustic impedance.  

There are many inversion techniques which are utilized in the industry for extraction of acoustic

impedance  from  post  stack  seismic  data, these  techniques  are  band-limited,  model  based,  and

neural network nonlinear inversions (Russell, 1988, Duboz et al., 1998, Keys and Foster, 1998,

Van Reil, 2000).

1.2 STATEMENT OF PROBLEM

The  global  energy  market  is  still  determined  to  get  more  oil  and  gas. Greater demands  for

hydrocarbon in recent  years caused oil and gas industry players to focus on deep offshore, and

hot areas around the world. Even by overwhelming the geographical challenges there still remain

serious challenging areas to deal with.  

In addition to collecting and evaluating data quickly and competently, another challenge in the

world of seismic exploration is the subsurface indistinctness which can be a difficult task in most

regions. The best appearance of the subsurface is always considered for more precise and low-

risk decision  making, to  reduce  drilling risk (dry  wells)  and  increase yield. Cutting-edge

techniques  provide enormous amount  of  information  that  can  help  to  address  the  challenges

which  improves  our  interpretation  of  subsurface  structures  and  also make  known more facts

about  hydrocarbon  prospects. Universal struggle for  hydrocarbon  continues  to motivate the

necessity to intensify exploration and boost recovery rate; nonetheless the cost of the operation is

critically essential.  

“Wells can measure several reservoir properties at high vertical resolution, but offer only sparse

sampling  laterally”,  often  at  considerable  cost  (Russell,  1988).  In  addition  difficulties  arise;

however,  when  we  encounter  poor  wellbore  condition  or  unexpected  lithology  or  complexities

related  to  subsurface  structure.  On  the  other  hand,  “seismic  data  provide nearly  continuous

lateral sampling at relatively low expense but with much less vertical resolution” (Russell, 1988).

To address the challenges, seismic inversion for estimating the elastic properties was introduced.

It is the latest advancement in an integration approach which is the inverse modeling of the logs

from seismic data.  

The  seismic  reflection  method  was  used  initially  as  a  useful  tool  for structure  identification;

some kind of structures could act as trap (such as anticline) for hydrocarbon reservoir (Russell et

al, 2006). So much efforts have been made to  improve our understanding  of the amplitudes of

seismic reflection data. It has been proved that a considerable amount of information is contained

in  seismic amplitude reflection that could  be connected with  porosity, lithology and even fluid

change within the subsurface (Russell et al, 2006). Though seismic amplitude is equally a good

indicator in the subsurface, several case studies depict that it is a vague indicator of hydrocarbon.

In  some  cases,  acoustic  impedance  alone  may not  be sufficient to  quantify  reservoir  rock

properties such as lithology and pore fluid, for an in-depth understanding of the reservoir.

In  order  to  obtain  more  accurate  seismic  reservoir  characterization  (also  known  as  reservoir

geophysics)  all  available  seismic, petro-physical and  geological  information need  to  be

integrated into volumetric distribution of reservoir properties like porosity and saturation. Each

of  them  has  a  piece  of information  which  assists  us  in delineating  or  describing  a  reservoir  or

monitoring the change (Walls et al, 2004).  

By  inversion,  we  convert  seismic  reflection  amplitude  to  impedance  profile  (rock  property

information) and estimate model parameters (in term of impedance instead of reflectivity). Using

inversion process, we try to “reduce discrepancies between observed and modeled seismic data”

(Russell,  1988).  The  main  objective  here  is  to  extract  underlying  geology  and  reservoir

properties from some set of observed seismic data to use for better lithology and fluid prediction

and prospect delineation (Russell, 1999). That is to say, the purpose is to obtain reliable estimate

of  P-wave  velocity,  S-wave  velocity and  density  to  calculate  the  physical  properties  and  the

earth`s structure.  

With  more  complex  geological  conditions  and  rise  in  cost  of  hydrocarbon  explorations,  the

inversion  technique  has  become  more  popular  and  is  widely  used  in  the  seismic  industry  for

exploration  and  development  of  existing  field.  Inversion  technique  is  a  useful  tool  to  derive

elastic properties such as P-impedance, bulk modulus, Poisson`s ratio and so forth, which largely

control the seismic response. As a result the outcomes we obtain from seismic inversion make up

better volumetric estimation (hydrocarbon anomalies are better predicted) than seismic attributes

derived from band limited seismic data (Connolly, 1999).

1.3 OBJECTIVE OF THE STUDY

In  seismic  inversion,  the  aim  is  to  transform  seismic  reflection  data,  which  are  interface-based

property, into a layer-based quantitative rock property, descriptive of the reservoir.  

In this work, an acoustic and elastic impedance volumes were inverted from near and far angle

stacks, respectively. The objective was to underscore which of these volumes was more effective

in litho-fluid delineation in a given well in the Niger Delta.  

1.4 SIGNIFICANCE OF THE STUDY

Seismic inversion enables the specialist to separate the seismic wavelet from the reflection series

characterized  by  the  geologic  formations  and  results  in  an  estimate  of  residual  impedance  for

each layer. Post-stack inversion is one alternative to conventional velocity analysis that provides

higher resolution by inverting for impedance from the reflection strength (Bell, 2002).

Inversion replaces the seismic signature by a blocky response, corresponding to acoustic and/or

elastic  impedance  layering.  It  facilitates  the  interpretation  of  meaningful  geological and  petro-

physical boundaries in the subsurface. Inversion increases the resolution of conventional seismic

in  many  cases  and  puts  the  study  of  reservoir  parameters  at  a  different  level.  It  results  in

optimized volumetric, improved ranking of leads/prospects, better delineation of drainage areas

and identification of ‘sweet spots’ in field development studies.

The ability to estimate acoustic impedance and a parameter related to shear impedance increases

the interpreter’s ability to discriminate between different lithologies and fluid phases, resulting in

a detailed reservoir characterization for improved hydrocarbon recovery.

1.5 SCOPE OF STUDY / LIMITATION

The  scope  of  this  project is  confined  to the  comparison of  acoustic  and  elastic  impedance

inversion for  rock  property  prediction. This  exercise  is  not  trivial,  however,  because  the  post-

stack inversion technique ignores the fact that offset-dependent behavior (amplitude vs. offset) is

buried in the stacked response and can cause significant perturbation of the results. One way to

overcome this limitation and also boost resolution of the results at the same time is to use only

the near-offset  traces for the analysis. This  is  a good method to  use because it provides higher

resolution  results  due  to  the  removal  of  far-offset  data  that  are  degraded  by  normal move-out

(NMO) stretch.

One of the challenges of inversion is that the method does not normally include a low-frequency

trend  for  velocity,  but  instead  predicts  variations  in  residual  impedance  that  must  be  separated

into velocity and density trends using well log data. Incorporating a low-frequency velocity trend

in  the  analysis  is  possible,  but  it  is  commonly  observed  that  the  low-frequency  trend,  where

combined  with  the  residual  impedances  on  the  seismic data,  does  not  match  the  predicted

impedances  from  well  logs.  Thus,  the  calibration  of  this  method  still  remains  a  limitation  in

many cases.

Seismic  inversion  is  not  a  unique  process.  There  are  several  acoustic  impedance  earth  models

that generate similar synthetic traces when convolved with the wavelet. The number of possible

solutions is significantly reduced by putting constraints on the modelling and, in doing so, a most

plausible scenario is retained. The support of other investigation techniques, like AVO analysis

and  forward  modelling,  increases  the  confidence  in  the  inversion  results. Seismic  inversion

depends heavily on the proper integration of well data. Seismic inversion is gradually becoming

a routine processing step in field development studies as well as for exploration purposes. Even

time  lapse  inversions  are  now  conducted.  The  positive  track  record  of  case  histories  clearly

demonstrates the added value of this type of seismic analysis (Curia D, 2009).  

1.6 STUDY AREA

Data used for this study were obtained from XY field, located in  Niger Delta offshore, several

kilometers  south  of  Port  Harcourt.    The  Niger  Delta  is  one  of  the  world’s  largest  and  sandiest

basins, situated on the West African continental margin at the apex of the Gulf of Guinea. It lies

between  latitudes  400N  and  600N  and  longitudes 300E and  900E,  and  covers  a  surface  area of

approximately 75,000 sq. km. Figure 1 below shows the location of the area.

.

SEISMIC INVERSION: COMPARISON OF ACOUSTIC AND ELASTIC IMPEDANCE INVERSION MODELS FOR ROCK PROPERTY PREDICTION



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