Application of in-situ anisotropic parameters in 3D seismic velocity analysis for improved pre-drill pore pressure prediction in the onshore Niger Delta basin, Nigeria

Asedegbega, Jerome; Opara, Alexander Iheanyichukwu; Emudianughe, J. E.; Omudu, Meshach

doi:10.1007/s12517-021-06725-z

Cited by 3 publications

(1 citation statement)

References 35 publications

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“…Eaton's formula may produce an error if the normal compaction trend line used for determining the normal hydrostatic pressure is not precisely drawn and accordingly corrections should take place (Chatterjee et al 2012). Simulation approaches that depend on the seismic log data were carried out to obtain a reliable model for pore pressure determination where an encouraging results were obtained (Asedegbega et al 2021). A recent study was performed for the goal of pore pressure determination using Artificial Neural Network (ANN) where this technique was successfully applied previously for the estimation of rate of penetration where reasonable results were produced (Markovic et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Developing a new approach for the anticipation of subsurface pressure in three oil wells from various fields in Iraq

Abbas

2021

J Petrol Explor Prod Technol

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Subsurface pressure quantification is the main goal for all drilling engineers due to its vital importance to minimizing drilling costs and preventing various excavating dilemmas such as stuck pipe, pipe collapsing, lost circulation, and well kick. Formation pressure is measured directly in producing hydrocarbon zones using special equipment; however, it is difficult to obtain pore pressure measurements in other intervals; therefore, many approaches were suggested and developed to anticipate the geopressure due to its importance on the drilling operation. Traditionally, Eaton's method is the most widely used for geopressure anticipation from well logs. In the current study, a new proposed formula for geopressure determination was derived from the modified Eaton's equation which is based on the inception of the mechanical specific energy. The study was applied on three oil-producing wells from different fields in Iraq (Missan C, West Qurna 15, and Zubair 171). The estimated subsurface pressure from the new suggested approach was validated by comparison with the actual in situ subsurface pressure obtained from Drill Stem Test (DST) and Repeated Formation Test (RFT). Statistical analysis is used for the validation by applying Mean squared error (MSE) and Mean Absolute percentage Error (MAE). Encouraging results were obtained from the present research for all wells being studied. The main finding of the current work is involving a new parameter (mechanical specific energy) for subsurface pressure determination, where it was not included in the previous techniques of geopressure equations. It was found that the value of exponent (m) in the new proposed equation has a significant influence on the predicted geopressure, where (m) varies from 0.1626 to 0.6896 depending on the type of the excavated rock plus the materials that the drill bit is manufactured of, where the interaction between these components is vital. The present work could be a useful method when planning to excavate a new well adjacent to the area of the investigated wells, where special well logs are unavailable for pore pressure measurement and suitable usage of mud weight is highly needed for the overall drilling process.

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Section: Introductionmentioning

confidence: 99%

Developing a new approach for the anticipation of subsurface pressure in three oil wells from various fields in Iraq

Abbas

2021

J Petrol Explor Prod Technol

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Lithofacies discrimination using seismic anisotropic attributes from logging data in Muglad Basin, South Sudan

Deng¹,

Hwang

Jang

2022

Open Geosciences

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The identification of formations in anisotropic reservoirs using seismic reflection data and logging data may lead to misrepresentations of the actual formations. Lithofacies discrimination intrinsically has ambiguity, and the depositional sequences of the study area comprise shales, fine-grained sands, and silts. So it needs to reduce the uncertainty of the lithofacies discrimination using anisotropic parameters. This study proposes an approach involving seismic anisotropic parameters to discriminate between different lithofacies. We calculate four anisotropic parameters (ε, δ, γ, η) from logging data (V p, V s, and density) and then employ these for lithofacies discrimination. We compared our results to lithofacies discrimination based on traditional parameters such as V p/V s ratio, clay volume, and water saturation. Using field data from Muglad Basin in South Sudan, we show how the suggested parameters could be used to identify eleven zones with distinct lithofacies. According to the anisotropic parameters, the lithofacies discrimination results are similar to other logging data, and it is easier to separate the lithofacies than petrophysical data. Furthermore, we introduce a new parameter, i.e., the difference between the normalized anisotropic δ parameter and clay volume, which can be used as a possible indicator for heavy oil reservoirs. The new parameter matches well with water saturation in the field data application.

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1D Pore Pressure and Geomechanics Models for Infill Well Drilling Optimization in CN Field, Offshore Niger Delta

Chukwudi,

Nwakanma,

Sofolabo

et al. 2024

SPE Nigeria Annual International Conference and Exhibition

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One of the significant challenges of hydrocarbon exploration especially in drilling campaigns is inaccurate well placement, leading to drilling unproductive wells and economically unviable opportunities in globally recognized petroleum-rich basins especially in our Niger Delta Basin, where since the effect of out-break of the global pandemic, drilling activities has decreased because of a whole lot of challenges. It is therefore of paramount importance to understand subsurface behaviour in planning wells, especially in a tectonically complex environment. The objective of the study is to employ pore pressure analysis and using geomechanics to evaluate wellbore stability in predicting mud-weight window and incorporating best practicing for accurate well placement to ensure minimum drilling risk and further reducing non-productive time (NPT). The workflow exploited five (5) parent wells investigating for the cause of overpressure in the field, building NCT and Overburden models, before estimating P10, P50, and P90 pore pressure models for the field. These models were also instrumental in estimating collapse pressure, shear failure gradient, maximum horizontal stress (SHmax) and fracture pressure/minimum horizontal stress (Shmin). From the offset wells using empirical relations suited for the field, 1D geomechanical model was constructed resulting in poisson's ratio (PR), unconfined compressive stress (USC), and friction angle (FA). Results from the pore pressure and geomechanics models informed our mud-weight selection, and to analyze wellbore strength prior to troublesome intervals. The mohr coulomb plot investigated the region of stability using the principal stresses, which revealed that at the understudied depths the well will not fail, further boosting our drilling confidence. From the study, the model boosted the analysis of the bedding plane failures, integrating a simulation of the existing stress profile. The analysis revealed the optimum mud-weight required to drill especially in reservoir depleted intervals. Consequently, future well placement and drilling can be done with minimal damage to the reservoir with negligible significance to wellbore instability concerns.

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Application of in-situ anisotropic parameters in 3D seismic velocity analysis for improved pre-drill pore pressure prediction in the onshore Niger Delta basin, Nigeria

Cited by 3 publications

References 35 publications

Developing a new approach for the anticipation of subsurface pressure in three oil wells from various fields in Iraq

Developing a new approach for the anticipation of subsurface pressure in three oil wells from various fields in Iraq

Lithofacies discrimination using seismic anisotropic attributes from logging data in Muglad Basin, South Sudan

1D Pore Pressure and Geomechanics Models for Infill Well Drilling Optimization in CN Field, Offshore Niger Delta

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