Establishing the Formation Pressure Profile of Predrill Well Based on Adjacent Wells Data

Similar documents
Predrill pore-pressure prediction using seismic data

Porosity Calculation of Tight Sand Gas Reservoirs with GA-CM Hybrid Optimization Log Interpretation Method

Seismic Response and Wave Group Characteristics of Reef Carbonate Formation of Karloff-Oxford Group in Asser Block

Application of Pressure Data Analysis in Tapping the Potential of Complex Fault Block Oilfield

Formation rock failure mode and its recognition method under high pressure squeezing condition in horizontal wells

The Seismic-Geological Comprehensive Prediction Method of the Low Permeability Calcareous Sandstone Reservoir

Quantitative Relation of the Point BarWidth and Meander Belt Width of Subsurface Reservoir

Characteristics of stratigraphic structure and oil-gas-water distribution by logging data in Arys oilfield

Study on the Couple of 3D Geological Model and Reservoir Numerical Simulation Results

Imaging complex structure with crosswell seismic in Jianghan oil field

So I have a Seismic Image, But what is in that Image?

Open Access Study on Reservoir-caprock Assemblage by Dual Logging Parameter Method

Drillworks. DecisionSpace Geomechanics DATA SHEET

Pressure Prediction and Hazard Avoidance through Improved Seismic Imaging

Wide/narrow azimuth acquisition footprints and their effects on seismic imaging

Prediction technique of formation pressure

Application of the Combination of Well and Earthquake in Reservoir Prediction of AoNan Area

Pore Pressure Estimation A Drillers Point of View and Application to Basin Models*

Formation Pore Pressure and Fracture Pressure Estimating from Well Log in One of the Southern Iranian Oil Field

Deterministic and stochastic inversion techniques used to predict porosity: A case study from F3-Block

Geophysical methods for the study of sedimentary cycles

Seismic Guided Drilling: Near Real Time 3D Updating of Subsurface Images and Pore Pressure Model

Pore Pressure Prediction and Distribution in Arthit Field, North Malay Basin, Gulf of Thailand

Automatic Drawing of the Complicated Geological Faults

Pore Pressure Prediction from Seismic Data using Neural Network

Effect Of The In-Situ Stress Field On Casing Failure *

Seismic Driven Pore Pressure Prediction

An Analytic Approach to Sweetspot Mapping in the Eagle Ford Unconventional Play

Main controlling factors of hydrocarbon accumulation in Sujiatun oilfield of Lishu rift and its regularity in enrichment

An integrated study of fracture detection using P-wave seismic data

Porosity. Downloaded 09/22/16 to Redistribution subject to SEG license or copyright; see Terms of Use at

Study on Build-up Rate of Push-the-bit Rotary Steerable Bottom Hole Assembly

Wellsite Consulting Services Diversified Well Logging LLC. All Rights Reserved.

The Improvement of 3D Traveltime Tomographic Inversion Method

The sensitivity of the array resistivity log to mud. inversion for improved oil water recognition

Applying Stimulation Technology to Improve Production in Mature Assets. Society of Petroleum Engineers

Study on Numerical Simulation of Steam Huff and Puff Based on Deformable Medium Model

American Journal of Energy Engineering

The Effect of Well Patterns on Surfactant/Polymer Flooding

Training Venue and Dates Ref # Reservoir Geophysics October, 2019 $ 6,500 London

International Journal of Scientific & Engineering Research, Volume 6, Issue 7, July ISSN

Application of seismic hydrocarbon detection technique to natural gas exploration-take Yingshan rift volcanic in the Yingcheng Groups as an instance

Seismic Velocities for Pore-Pressure Prediction. Some Case Histories.

I. INTRODUCTION 1.1. Background and Problem Statement

Geohazards have a direct impact on the drilling and

Process, Zeit Bay Fields - Gulf of Suez, Egypt*

The elastic properties such as velocity, density, impedance,

NEW DEMANDS FOR APPLICATION OF NUMERICAL SIMULATION TO IMPROVE RESERVOIR STUDIES IN CHINA

Modeling of 3D MCSEM and Sensitivity Analysis

The Analytic Hierarchy Process for the Reservoir Evaluation in Chaoyanggou Oilfield

Integrating Geomechanics and Reservoir Characterization Examples from Canadian Shale Plays

Practical Geomechanics

Evaluation on source rocks and the oil-source correlation in Bayanhushu sag of Hailaer Basin

Enhanced Subsurface Interpolation by Geological Cross-Sections by SangGi Hwang, PaiChai University, Korea

SEG Houston 2009 International Exposition and Annual Meeting

Downloaded 01/06/15 to Redistribution subject to SEG license or copyright; see Terms of Use at

Reservoir properties inversion from AVO attributes

The Mine Geostress Testing Methods and Design

Best practices predicting unconventional reservoir quality

Improved Exploration, Appraisal and Production Monitoring with Multi-Transient EM Solutions

Estimation of shale reservoir properties based on anisotropic rock physics modelling

Ingrain Laboratories INTEGRATED ROCK ANALYSIS FOR THE OIL AND GAS INDUSTRY

Simultaneous Inversion of Clastic Zubair Reservoir: Case Study from Sabiriyah Field, North Kuwait

3D modeling of subsurface geo-objects with netty-cross sections in engineering geology

A new model for pore pressure prediction Fuyong Yan* and De-hua Han, Rock Physics Lab, University of Houston Keyin Ren, Nanhai West Corporation, CNOOC

Today s oil is yesterday s plankton

Petroleum Exploration

Drilling Technology - The Emergence of New Risk, From A Loss Adjuster's Perspective

Characterization of Pore Structure Based on Nondestructive Testing Technology

Integrating rock physics and full elastic modeling for reservoir characterization Mosab Nasser and John B. Sinton*, Maersk Oil Houston Inc.

Time-lapse seismic modelling for Pikes Peak field

A research on the reservoir prediction methods based on several kinds of seismic attributes analysis

IJMGE Int. J. Min. & Geo-Eng. Vol.49, No.1, June 2015, pp

3D Geological Modeling and Its Application under Complex Geological Conditions

Distribution of Overpressure and its Prediction in Saurashtra Dahanu Block, Western Offshore Basin, India*

Multi-skill software for Planning, Following-Up and Post Analysis of wells.

We Simultaneous Joint Inversion of Electromagnetic and Seismic Full-waveform Data - A Sensitivity Analysis to Biot Parameter

The effect of anticlines on seismic fracture characterization and inversion based on a 3D numerical study

Search and Discovery Article # (2015) Posted April 20, 2015

Fr CO2 02 Fault Leakage Detection From Pressure Transient Analysis

Fractured Volcanic Reservoir Characterization: A Case Study in the Deep Songliao Basin*

Economic Geology Unconventional Energy Research

Logging characteristic analysis of basalt in eastern depression of Liaohe Oilfield

Main Challenges and Uncertainties for Oil Production from Turbidite Reservoirs in Deep Water Campos Basin, Brazil*

Chinese Petroleum Resources / Reserves Classification System

Influence of Drilling Fluid Density on Deep-water Well Structure Design

Velocity Update Using High Resolution Tomography in Santos Basin, Brazil Lingli Hu and Jianhang Zhou, CGGVeritas

DETERMINING THE SATURATION EXPONENT BASED ON NMR PORE STRUCTURE INFORMATION

Block 43B - Onshore Oman

Time-lapse (4D) seismic effects: Reservoir sensitivity to stress and water saturation

The layered water injection research of thin oil zones of Xing Shu Gang oil field Yikun Liu, Qingyu Meng, Qiannan Yu, Xinyuan Zhao

Subsurface Mapping 1 TYPES OF SUBSURFACE MAPS:- 1.1 Structural Maps and Sections: -

Stratigraphic Trap Identification Based on Restoration of Paleogeophology and Further Division of System Tract: A Case Study in Qingshui Subsag*

Numerical Simulation of the Oil-water Distribution Law in X Block Geology by Using the STARS Mode

23855 Rock Physics Constraints on Seismic Inversion

Summary. Simple model for kerogen maturity (Carcione, 2000)

Maximize the potential of seismic data in shale exploration and production Examples from the Barnett shale and the Eagle Ford shale

Study of early dynamic evaluation methods in complex small fault-block reservoirs

Pressure Analysis of ZK212 Well of Yangyi High Temperature Geothermal Field (Tibet, China)

PETE/GEOS 445/645 Petroleum Geology 3 credits

Transcription:

Journal of Applied Science and Engineering, Vol. 19, No. 2, pp. 207 213 (2016) DOI: 10.6180/jase.2016.19.2.11 Establishing the Formation Pressure Profile of Predrill Well Based on Adjacent Wells Data Ya-Nan Sheng 1 *, Zhi-Chuan Guan 1 and Kai Wei 2 1 Department of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, P.R. China 2 Bohai Drilling Technology Service Company, Tianjin 300280, P.R. China Abstract The formation pressure plays a very important role in drilling engineering. So it is of great significance to predict formation pressure before drilling. In order to solve the problem, the concept of formation matrix and wellbore matrixwere put forward. Also the method of epitaxial transplantation for the regional formation pressurewas proposed. With the concept of wellbore pressure matrix, the target wellbore pressure matrix can be builtby dealing with the adjacent wellborepressureusing the method of depth adjustment and weighted distance correction. Finally, we can obtain the formation pressure of the targetwell. Case study of Qinghai Oilfield was carried out to test the method. Through comparative analysis, the maximum relative error of the transplantation pressure and logging interpretation pressure is 4.2%. The result indicated that the accuracy and reliability of the method can meet the engineering requirement. This is conductive to designers to predict formation pressure which can provide the basis for the casing design and the selection of the drilling fluid density. Key Words: Formation Pressure, Formation Matrix, Wellbore Matrix, Epitaxial Transplantation Method 1. Introduction *Corresponding author. E-mail: shengyanan_upc@163.com The formation pressure is the basic data of the exploration, development and construction. It is of great importance to predict the formation pressure accurately [1]. Currently, we normally predict the formation pressure according to the seismic or logging data [2]. The most commonly used method is Eatonlaw [3]. For a new development field, the seismic data is the only data that can be used. Pennebaker summed up a method of predicting the formation pressure based on the seismic data in 1968 [4]. Since then, many methods had been established, such as Eatonlaw [5], Dutta law [6] and Fillipponelaw [7]. The Fillippone law has been widely used because of the high accuracy and the wide applicability. Many experts improvedthe method of predicting the formation pressureon the basis of the Fillippone law. Martinez proposed the iterative simulation, which can predict the formation pressure more accurately [8]. Seismic data is one of the few materials which can be obtained before drilling. In most cases, there is no choice to predict the formation pressure according to the seismic data [9]. However we can get rich data of the drilled adjacent wells such as logging data andcore data in the mature block. So we can use the adjacent well data to predictthe target predrill wellformation pressure. Then the formation pressure of any depth can be calculated by the epitaxial transplantation method [10]. In the absence of regional seismic data, this paper established the wellbore pressure matrix of the target well by using the drilled adjacent wellbore data. Itincludes the formation depth and formation pressurewhich are in the target formation

208 Ya-Nan Sheng et al. group. It can provide important information and theoretical basis for the design of geological drilling, the casingprogram and the selection of the drilling fluid density. By comparing the transplantation pressure with logging interpretation pressure,we can reach the conclusion that the accuracy of this method can meet the engineering requirement. The method consists of the following steps: Analyze the spatial distribution of the target formation; Build the adjacent wellbore pressure matrix in this area; Deal with the adjacent wellbore pressure matrix by the depth adjustment; Build the target wellbore pressure matrix by using the weighted distance correction algorithm. spatial distribution of the regional formation. Considering the above factors, this paper proposed the concept of wellbore matrix including the wellbore depth and wellbore data. The wellbore matrix is the application of the formation matrix in the direction of the well depth. The wellbore matrix is consisted of well depth and wellbore data. In case of formation pressure,the form of wellbore pressure matrix as formula 1: (1) 2. The Formation Matrix The digital formation is a comprehensive research system which is gradually developed with the research of the 3D digital GIS [11], geological modeling [12] and 3D visualization in drilling operations [13]. The digital formation is a four-dimensional concept. For the formation of point I, it has two properties: the spatial position and geological parameters. So we can describe the feature of point I with the use of the array (x i, y i, z i, p i ). x i, y i, z i is the spatial position of point i, p i is the geological parameter of point i. In order to realize the scientific management and application of the digital formation, this paper putforward the concept of the formation matrix. The formation matrix refers to the matrix of the spatial position of the formation and geological property parameters. Under the Cartesian coordinates, the formation matrix consists of four matrixes: X, Y, Z, P, which representthe position matrix in the direction of x, y, z and the matrix of the attribute parameters. Each of them is a three-dimensional matrix and the numbers of their basis vectors are equal. When we build the formation matrix, we should firstly divide the formation by assuming the x direction being divided into m points, the y direction being divided into n points and the z direction being divided into k points. Figure 1 shows the formation matrix: The formation pressure in the area changes greatly. It is influenced by the ups and downs and thickness of the formation group and extension trends of the fault. So when we use the data of the adjacent wells to predict the target well pressure, we need to take full account of the The wellbore pressure matrix includes the formation depth matrix H and the pressure matrix P. The depth matrix H stands for the position matrix in the direction of well depth. The pressure matrix P indicates the corresponding formation pressure. The superscript x indicates the well number and the subscript i indicates one layer of the formation, the subscript m indicatesthe data point number in the i-th layer. The first column is the stratigraphic burial depth, and the second column is the corresponding formation pressure. p i 1, p i, p i+1, respectively denotes the wellbore pressure matrix of adjacent layers (i 1), i,(i + 1). The target wellbore pressure matrix contains the depth of the target formation and its formation pressure, so the wellbore pressure matrix can accurately describe Figure 1. Formation matrix.

Establishing the Formation Pressure Profile of Predrill Well Based on Adjacent Wells Data 209 the depth of the target formation and the formation pressure in the area. 3. Epitaxial Transplantation Method of Regional Formation Pressure Assuming there are N drilled and adjacent wells in the region, we can build the wellbore pressure matrix of the N wells at the target formation according to the concept of the wellbore pressure matrix. Then by the following theoretical method and procedurethe wellbore pressure matrix of the target well in the region can be established. The flow sheet of the algorithm is shown as Figure 2: 3.1 Division of the Target Well s Stratigraphic Section The terrain generation technology is one important research area of GIS. It mainly studies simplification, generation and display of the digital terrain model. In geology, formation is mostly given in the form of contour lines. Establishing the spatial distribution of the regional formation is the important basis for the description of the regional formation pressure. By the comprehensive analysis of logging data, lithological data and geological information of the drilled wells, we will get the well deployment, geological stratification and graphic data. Then we can use the terrain generation technology to establish the three-dimensional spatial distribution of the regional formation. Depending on it, we can get the stratigraphic division of the adjacent and the target well in the area. The top and bottom boundary of the i-th layerof the adjacent well and the target well are expressed as F xi = (H x iu, H x id ) F oi =(H iu o, H id o ) (Figure 3). If the formation has M sections, the stratigraphic matrix of the adjacentwell and the target well is as follows: (2) We can build the stratigraphic matrix of the adjacent well according to the well report. Then the contour of the top and bottom boundary of the layers can be obtained based on the stratigraphic matrix of the adjacent well. At last, the division of geologic position of the target well can be gotten. 3.2 Calculation of the Target Wellbore Pressure Matrix 3.2.1 Depth Adjustment Method The formation depth has a great impact on the formation pressure of the target well. However, the drilled wells and the target well have scarcely the save burial depth. It can be achieved by dealing with the adjacent wellbore pressure matrix. The x-th wellbore pressure x matrix turns to p i by this method: Figure 2. Algorithm diagram of extension and transplantation method. Figure 3. Diagram of the regional stratigraphic spatial distribution.

210 Ya-Nan Sheng et al. (3) pressure matrix has different distance after the depth adjustment and the correction of the weighted distance. It is becausethat the depth and thickness of the adjacent wells and the target well are different. So the formation depth matrix of the adjacent wellbore pressure matrix needs to be converted to the target well formation depth matrix. While the column vectors of the pressure matrix should be interpolated. Finally we got the i-th lay wellbore pressure matrix of the target well: 3.2.2 Correction of the Weighted Distance The distance between the adjacent wells and the target well has impact on formation pressure because the rock interior is continuous. Assuming that the coordinates of the adjacent wells is (X x, Y x ), x = 1, 2,, N and the coordinates of the target wells is (X O, Y O ). According to the inverse-weighted distance interpolation (Shepard method) [14], the x-th wellbore pressure matrix in the i-th lay of the target well is: (5) 4. Example (4) 2 2 d x = ( X O X x) ( YO Yx) is the horizontal distance from point (X O, Y O ) to point (X x, Y x ), x = 1, 2,, N. The t which is called the weighted exponent is a constant greater than 0. It can adjust the shape of the surface of the interpolation function. The surface at the function node is sharper when t is smaller. 3.2.3 Building the Target Wellbore Pressure Matrix The formation depth matrix of the adjacent wellbore NiuDong Block has been the focal point of Qinghai oilfield in recent years. Because of the complex geological conditions, it is difficult to predict the formation pressure. The vague understanding of the formation pressure caused various drilling risks mainly including the lost circulation, kick, collapse and stick. So we regard the area of Qinghai Oilfield as the target area in this paper in order to verify the reliability of the method. There are five vertical wells in this area. The coordinates of well location is shown in Figure 4. The top and bottom bounds of the target stratumare shown in Table 1. To verify the reliability of the method, we choose one of five drilled wells as the target well and the restfour as the drilled adjacent wells. Firstly, we calculated the formation pressure of the four drilled adjacent wells in the target formation based on the Eaton law by using the logging data. According to the calculation results, the wellbore pressure matrix of adjacent wells can be constructed. The left panel in Figure 5 shows the distribution of the adjacent wellbore

Establishing the Formation Pressure Profile of Predrill Well Based on Adjacent Wells Data 211 Table 1. The bound of the targetstratum Well Top depth/m Bottom depth/m N102 1620 2160 N104 1600 2090 N1-2-10 1424 1928 N2 1340 2160 Target 1524 2050 Figure 4. Wells coordinate. pressure in the target stratum. Secondly, we got thedepth adjustment results of adjacent wellbore pressure based on the Equation (3). The results are shown onthe right panelof Figure 5. Then the target wellbore pressure can be gotten by using the Equations (4) and (5). Finally, we got the transplantation pressure of the target well. To verify the reliability of the method, we calculated the formation pressure of the target well based on the logging date. Then, we calculated the epitaxialtransplantation pressure of the target well by using the method which was proposed in this paper. The dotted line in the Figure 6 represents the result of the transplantation pressure and the solid line stands for the result oflogging interpretation pressurecalculated bythe Eaton law. As is shown in Table 2, the maximum relative error of the transplantation pressure and logging interpretation pressure is 4.2%. Through the analysis, we can reach the conclusion that the accuracy of this method can meet the engineering requirement. 5. Conclusions (1) The concept of the formation matrix and the wellbore matrix were put forward. The matrix includes stratigraphic information and geological parameter information which can help us to grasp the distribution of the geological parameters accurately. (2) The epitaxial transplantation method was built. With Figure 5. Formation pressure and its depth-adjustment results of adjacent wells.

212 Ya-Nan Sheng et al. Figure 6. Comparison of transplantation pressure and logging interpretation pressure. Table 2. Verification of the algorithm precision Depth (m) Transplantation pressure Logging interpretation pressure the concept of wellbore pressure matrix, we can build the target wellbore pressure matrix by dealing with the adjacent wellbore pressure matrixby the method of depth adjustment and weighted distance correction. The method regards the formation group as the basic unit. So it can not only consider the impaction of the adjacent wells but also reflect the spatial characteristics of formation pressure. Results of the case study indicated that the accuracy and reliability of the method can meet the engineering requirement. (3) The wellbore data, spatial location and spatial continuity of the adjacent wells are key factorsfor impacting the calculation accuracy. For the area which has faults or complex geological structures, utilizing the 3D seismic data to improve the calculation accuracy of formation pressure is the research direction. Acknowledgment Error 1550 1.22 1.24 1.6% 1700 1.24 1.19 4.2% 1800 1.30 1.26 3.2% 1900 1.51 1.49 1.3% 2000 1.15 1.20 4.1% The authors would like to acknowledge the academic and technical support of China University of Petroleum (East China). This paper is supported by the National Natural Science Foundation of China (No. 51574275) and the Graduate Innovation Project Foundation (CX2013011) and the National High Technology Research and Development Program ( 863 Program) of China (2012AA091501). References [1] Feral, W. H., Abnormal Formation Pressure, Implication to Exploration, Drilling and Production of Oil and Gas Reservoirs, Amsterdam: Elsevier (1976). [2] Drilling Handbook (Party A) Writing Group. Drilling Handbook (Party A): First Volume, Beijing: Petroleum Industry Press, pp. 43 86 (1990) (Chinese). [3] Eaton, B. A., The Equation for Geopressure Prediction from Well Logs Fall Meeting of the Society of Petroleum Engineers of AIME, Society of Petroleum Engineers (1975). doi: 10.2523/5544-MS [4] Pennebaker, E. S., Seismic Data Indicate Depth, Magnitude of Abnormal Pressure, World Oil, Vol. 166, No. 7, pp. 73 78 (1968). [5] Eaton, B. A., Graphical Method Predicts Geopressures Worldwide, World Oil, (United States), Vol. 183, No. 1 (1976). [6] Dutta, N. C., Deepwater Geohazard Prediction Using Prestack Inversion of Large Offset P-wave Data and Rock Model, The Leading Edge, Vol. 21, No. 2, pp. 193 198 (2002). doi: 10.1190/1.1452612

Establishing the Formation Pressure Profile of Predrill Well Based on Adjacent Wells Data 213 [7] Fillippone, W. R., On the Prediction of Abnormally Pressured Sedimentary Rocks from Seismic Data, Offshore Technology Conference Houston, Texas, April 30 May 3 (1979). doi: 10.4043/3662-MS [8] Martinez, R. D., Deterministic Estimation of Porosity and Formation Pressure from Seismic Data, 1985 SEG Annual Meeting, Society of Exploration Geophysicists (1985). doi: 10.1190/1.1892593 [9] Sayers, C. M., Johnson, G. M. and Denyer, G., Predrill Pore-pressure Prediction Using Seismic Data, Geophysics, Vol. 67, No. 4, pp. 1286 1292 (2002). doi: 10.1190/1.1500391 [10] Pei, X. and He, Q., Formation Pressure Prediction of Adjustment Wells Using Adjacent Wells Data, Fault- Block Oil & Gas Field, No. 2, pp. 26 28 (1994) (Chinese). [11] Zhang, J.-X., Liu, J. and Li, D.-R., Technical Approach to Realistic Terrain Generation, Journal of Image and Graphics, No. 8/9, pp. 638 645 (1997) (Chinese). [12] Wu, Q., Xu, H. and Zou, X., An Effective Method for 3D Geological Modeling with Multi-source Data Integration, Computers & Geosciences, Vol. 31, No. 1, pp. 35 43 (2005). doi: 10.1016/j.cageo.2004.09.005 [13] Victor, J., Taking Advantage of 3-dimensional Visualization in Drilling Operations, SPE/IADC Drilling Conference, Amsterdam, Netherlands, March 4 6. doi: 10.2118/37591-MS [14] Zhang, J., Guo, L. and Zhang, X., Effects of Interpolation Parameters in Inverse Distance Weighted Method on DEM Accuracy, Jouranl of Geo-matics Science and Technology, No. 1, pp. 51 56 (2012) (Chinese). Manuscript Received: Oct. 30, 2015 Accepted: Apr. 12, 2016