Using legacy seismic data in an integrated time-lapse study: Lena Field, Gulf of Mexico

Johnston, David H.; Eastwood, John; Shyeh, J. Jane; Vauthrin, Robert; Khan, Mashiur; Stanley, Larry R.

doi:10.1190/1.1438596

Cited by 22 publications

(8 citation statements)

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“…Because of this, the inversions could not be posed to deterministically estimate spatial distributions of pore pressure and saturation from pre-stack seismic data. Work reported by Johnston et al (2000), Landro The work presented in this Section strongly suggests that inversion of single-time prestack seismic data could be used to benchmark and quantitatively relate seismic amplitude variations in time with dynamic reservoir changes due to production. Inversion provides a unique framework to assess (a) the quality and reliability of seismic data and (b) the sensitivity of changes in petrophysical parameters due to changes in elastic parameters.…”

Section: A3554 Evaluation Of Resultsmentioning

confidence: 94%

Integrated Approach for the Petrophysical Interpretation of Post-and Pre-Stack 3-D Seismic Data, Well-Log Data, Core Data, Geological Information and Reservoir Production Data via Bayesian Stochastic Inversion

Torres‐Verdín¹,

Sen²

2004

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The present report summarizes the work carried out between September 30, 2000 and September 30, 2004 under DOE research contract No. DE-FC26-00BC15305. During the three-year project period, we carried out extensive studies on the inversion post-stack and pre-stack data together with well logs, petrophysical information and fluid flow data. We have achieved all the project goals including development of algorithm for joint inversion of pre-stack seismic data, well logs, and time records of fluid production measurements using stochastic inversion algorithms which were demonstrated on realistic synthetic and field data. Our accomplishments are:• Joint inversion of post-stack seismic, well log, fluid flow, and petrophysical data: we demonstrated the technique with application to data from the Gulf of Mexico.• Development of a robust pre-stack full waveform inversion algorithm: A new approach based on iteration-adaptive regularization that makes use of plane wave transformed seismic data, was developed and applied to OBC dataset from the Gulf of Thailand. The algorithm was also implemented on a cluster of personal computers.• Joint inversion of pre-stack seismic and well-log data: A new stochastic optimization algorithm that makes use of the essential features of seismic and well log data was developed and tested on realistic synthetic dataset.• Joint inversion of pre-stack seismic and fluid flow data: A novel technique was developed to optimally combine seismic and flow data. The technique makes very realistic estimate of porosity; sensitivity of the flow parameters to two disparate datasets was studied extensively. DE-FC26-00BC15305iv • Direct estimation of petrophysical parameters from seismic data: The pre-stack waveform inversion was modified to invert directly for porosity and saturation using the BiotGassmann equation at each iteration step.The final report contains abridged versions of some of our inventions. The works resulted in several peer-reviewed publications. Five papers have been communicated for peer-reviewed publication, and seven papers were presented at conferences. All of these publications and presentations stemmed from work directly related to the goals of our DOE project.

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Section: A3554 Evaluation Of Resultsmentioning

confidence: 94%

Integrated Approach for the Petrophysical Interpretation of Post-and Pre-Stack 3-D Seismic Data, Well-Log Data, Core Data, Geological Information and Reservoir Production Data via Bayesian Stochastic Inversion

Torres‐Verdín¹,

Sen²

2004

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“…Ertekin et al 23 stated that reservoir simulation and modeling might be the only reliable method to predict performance of large complex reservoirs. This assertion was supported by Johnston et al 24 that a reservoir simulation and modeling when combined with three-dimensional (3D) time-lapse seismic results can be used to monitor past and future production performance. The major goal of reservoir simulation is to predict future performances of reservoirs and find ways and means of optimizing the recovery of hydrocarbons under various operating conditions.…”

Section: Andmentioning

confidence: 86%

Computer modeling and simulation for undersaturated primary drive recovery mechanism

Gyan

Xie

Brantson

et al. 2019

Advances in Mechanical Engineering

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The focus of this article is to test the capability of a three-dimensional undersaturated numerical reservoir simulator developed for prediction of actual field performance cases. The simulator development employs unconditional stable Crank-Nicolson second order in time approximation discretization scheme and preconditioned conjugate gradient iterative solver for the derived fluid flow equation. Furthermore, formation volume factor as a function of cell pressure is computed at each time step until bubble-point pressure is reached. The reservoir model is then coupled with a horizontal wellbore model in the simulator by placing a well optimally at the center of its drainage volume. The numerical simulation results show that the numerical solutions improve significantly with the addition of grid blocks. Graphical visualization surface and contour map plots show rapid and continuous average reservoir pressure depletion with time for an earliest possible determination and characterization of primary drive mechanisms. The rate of pressure depletion and recovery factor estimation (1.52%) are the two main characteristics used to identify depletion drive or rock and liquid expansion drive as the best-fit prospective drive for the reservoir model. The total cumulative production of 170,000 stock-tank barrels (MSTB) recovered in 1390 days is in agreement with the field data used. Sensitivity analyses with the numerical simulator illustrated the key impact of reservoir parameters on pressure depletion with less computational expensiveness. Finally, material balance incremental (0.995) and cumulative (1.005) error checks validate the simulator robustness within an acceptable tolerance limit.

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“…These steps provided an improved 4D match without overly conditioning the data, as the seismic data had been co-processed and matched for 4D purposes by the seismic processing contractor. It is important to note that the degree of cross equalization required, and its ultimate success, depends on the consistency in acquisition and in prior processing of the baseline and monitor surveys (Johnston et al, 2000). To test if the workflow improved the 4D signal, the repeatability was calculated before and after each cross equalization step was applied.…”

Section: Cross Equalizationmentioning

confidence: 99%

4D simultaneous PP-PS prestack inversion in the Edvard Grieg field, Norwegian North Sea

Daneshvar

Simmons

Todd

et al. 2020

SEG Technical Program Expanded Abstracts 2020

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Using legacy seismic data in an integrated time-lapse study: Lena Field, Gulf of Mexico

Cited by 22 publications

References 0 publications

Integrated Approach for the Petrophysical Interpretation of Post-and Pre-Stack 3-D Seismic Data, Well-Log Data, Core Data, Geological Information and Reservoir Production Data via Bayesian Stochastic Inversion

Integrated Approach for the Petrophysical Interpretation of Post-and Pre-Stack 3-D Seismic Data, Well-Log Data, Core Data, Geological Information and Reservoir Production Data via Bayesian Stochastic Inversion

Computer modeling and simulation for undersaturated primary drive recovery mechanism

4D simultaneous PP-PS prestack inversion in the Edvard Grieg field, Norwegian North Sea

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