An optical fiber has been utilized to continuously acquire liquid production profiles in horizontal well in X oilfield. The results obtained from the dynamical monitoring system confirm the time-varying law of the physical property under the condition of high-water flooding, which can serve as the guidelines to explore the potential of remaining oil in high water-cut/high recovery factor oilfield.
Usually, the sound wave shows different propagation speeds in different medium, which is the basic principle of this test. Firstly, optical cable is used for sound wave detection and signal demodulation.Meanwhile, a series of other processes are applied to calculate the sound velocity of mixed medium; Then the volume velocity and holdup of mixed medium for each phase are determined.The measure of liquid-producing profile along the whole horizontal well has been realized in real time. Finally, numerical simulation model considering the time-varying physical properties is established based on the core flooding laboratory experiment. This result will provide guidelines for the exploration of remaining oil in the well.
The results obtained from optical fiber monitoring system during last two years show that 80% of the fluid produced from the 502-meter horizontal well is mainly contributed to the first 90-meter horizontal section. Experimental results of core flooding under excessive water flooding (2000 pore volume) indicate that the permeability is 1.4 times of the original. The results of numerical simulations considering the time-varying physical properties illustrate that there is still internal remaining oil along the horizontal well section. So, the strategy of exploiting potential oil is proposed using an accurate directional water plugging, which will decrease 10% water cut and obtain more recoverable reserves.
Based on the dynamical monitoring results of optical fiber, this paper innovatively provides the strategy of exploiting potential remaining oil in the horizontal wells, which can provide a valuable suggestion for offshore oilfield with high productivity at high water-cut stage.
Alternating high and low concentration polymer flooding has been proposed and applied in some offshore oilfields to improve polymer flooding efficiency, but the research of pressure analysis in alternating polymer flooding reservoir is rare, this work presents a numerical pressure analysis method of three-zone composite model for formation evaluation. The type curves have seven regimes in three-zone composite model. The characteristic is the obvious upturn of pressure derivative curve in transient regime between high concentration and low concentration polymer solution. Formation parameters can be interpreted by history matching and formation evaluation can be conducted based on this model. As an important part of formation evaluation, formation damage as a result of adsorption of polymers in porous media is evaluated by comparing the interpreted permeability with the original value before polymer flooding. The field test data proves that this proposed method can accurately evaluate reservoir characteristics in alternating polymer flooding reservoirs, which emphasizes the potential application of this method in petroleum industry.
BZ field is located at Bohai Bay of China, it is featured with multiple complex fluvial reservoirs with small lateral extension (100-300m wide) and thin accumulation (6-12m). Many channels are isolated and poorly connected across the field. As a result of the fluvial narrowness, low reserve abundance and limited natural energy, the development of this field was tied back into the neighboring field facilities and was categorized as the marginal value field with low ROR (rate of return). This paper presents a successful implementation of the flowchart of "adjust while drilling" to tap these kinds of reservoirs during the E&P circles.
In the ODP design phase, 13 well slots were reserved for the future use. And the overall geological characteristics is predicted to be much complex.
In order to mitigate risks, identify potential opportunities and improve the benefit of plan, a work flow integrating seismic, geology, logging and productivity forecast, with exploration concepts was designed during development phase to optimize drilling schemes.
The process is divided into 5 steps: 1. Locate and characterize key sands by combined analysis of logging and seismic data. 2. Recognize hydrocarbon migration pattern, identify potential oil-bearing sands, and estimate OOIP; 3. Design well patterns and forecast productivity based on the reservoir characteristics and OOIP. 4. Optimize drilling sequence and well trajectory; evaluate reservoir potential and risks based on data from drilled wells, and then optimize future well locations. 5. Apply logging while during drilling (LWD) and Periscope to reach optimal landing point and ensure high NTG.
Modifications to the ODP mainly include: 1. Staggered line well pattern was adopted to develop single story channel. 2. A large number of horizontal wells were adopted. 3. Understanding on the relationship between production wells and injection wells were improved by placing the deviated injection wells at the multi-stored channel stacking. And the well spacing was determined based on the updated reservoir properties to warrant waterflood sweeping conformance and efficiency. 4. Newly proved potentials were targeted through remaining reserved slots.
Through this process, OOIP has increased by 108%, production well counting has risen from 19 to 32, locations of 9 wells reserved during ODP phase have been successfully optimized and redirected; independent P-I pairs have been positioned for each single story channel with the P-I ratio over 90% and good response between those pairs. Average productivity has reached 1.5 times of the designed level.
The overall successful development of BZ field has proved the effectiveness of the flowchart, which is designed for the risk mitigation, potential tapping, slot utilization and financial performance enhancement. Therefore, it provides an insightful guidance for the future similar reservoirs development program design.
The survey with shallow reef is located at the Pearl River Mouth Basin of South China sea. Water depth is around 100 meters but variable across the survey. The shallow reef is in the middle of survey. It is about 14km width and 10km length spatial size. With such huge spatial size, it had posed big challenges to subsurface reservoir imaging.
Firstly, the variable water bottom generates complicated water layer related multiples, especially at the shallow reef area. Meanwhile, with limited near offset information in the legacy NAZ data, accurate water layer multiple model is very difficult to predict with conventional methods.
Secondly, the shallow reef mainly composed of carbonates, which have higher velocity compared to surrounding sediments. This high velocity carbonates thus cause severe distortion to the wave field propagated through and severely distorted the underlying reflections. Without correct imaging of reef at shallow, little confidence can be brought to deeper structures imaging, and interpretation.
Least-squares migration (LSM) has become an increasingly important imaging tool in the seismic industry. It can successfully address imaging issues related to insufficient illumination and mitigate both migration artifacts and noise. More recently, a number of case studies from around the world have shown that LSM provides greatly improved seismic imaging. However, only a few examples reveal its advantages in both imaging and amplitude-versus-offset (AVO) inversion. For the amplitude aspect, compensating the effect of anelastic absorption and elastic scattering during propagation inside the earth has become increasingly popular over the past few years. The anelastic absorption and elastic scattering causes frequency-dependent amplitude decay, phase distortion, and resolution reduction. This is often quantified by the quality factor commonly called Q model. This effect can be largely compensated through Q prestack depth migration (QPSDM). Therefore, QPSDM has become an effective solution for seismic imaging in areas where strong absorption anomalies exist in the overburden. However, the excessive noise often resulting from QPSDM poses a big challenge to its application. In this paper, we propose a least-squares Q migration (LSQM) method that combines the benefits of both LSM and QPSDM to improve the amplitude fidelity and image resolution of seismic data. We also demonstrate that both seismic imaging and AVO inversions at wells can be significantly enhanced through image-domain single-iteration least-squares QPSDM Kirchhoff migration.
Chen, Li (Schlumberger) | Gan, Yunyan (CNOOC) | Gao, Bei (Schlumberger) | Chen, Jichao (Schlumberger) | Canas, Jesus A. (Schlumberger) | Jackson, Richard (Schlumberger) | EI-Khoury, Jules (Schlumberger) | Mullins, Oliver C. (Schlumberger)
Reservoir connectivity is always the major concern for reservoir evaluation. In addition, reservoirs exhibit all manners of complexities that introduce many other production concerns such as aquifer support, viscous oil, low productivity index, and high AOP. Improved methods of reservoir evaluation are needed. A new discipline Reservoir Fluid Geodynamics (RFG) provides a powerful framework to significantly improve reservoir understanding and naturally allows substantial data integration across many discipline. Many reservoir fluids have been altered by reservoir fluid geodynamic (RFG) processes such as a late gas charge, asphaltene migration, biodegradation, water washing, which complicate fluid distributions and produces extra challenges to understand connectivity and other reservoir concerns. Identifying and quantifying the alteration processes will be key issues addressed herein. This RFG approach also helps to clarify complexities associated with reservoir concerns such as asphaltene stability, composition gradients, viscosity variations, tar mat formation, and fault block migration.
This paper describes an integrated approach within an RFG framework to understand reservoir connectivity and fluid alteration processes. This approach is founded on simple asphaltene thermodynamics and the ability to identify fluid equilibration utilizing the Flory-Huggins-Zuo Equation of State (FHZ EoS) with its reliance on the Yen-Mullins model. This model classifies the asphaltene species dispersed in crude oil in 3 different forms: molecules, nanoaggregates (of molecules) and clusters (of nanoaggregates). For low concentrations of asphaltenes, they are present in crude oils as a true molecular solution and corresponds to the Light Oil Model. At higher asphaltene concentrations, they are present as nanoaggregates giving the Black Oil Model and at even higher concentrations, they are present as clusters giving the Heavy Oil Model. Gas charge into reservoirs can destabilized asphaltenes and can change their colloidal description causing a transition in the appropriate model for describing asphaltene (and viscosity) gradients. Continued asphaltene instability can yield tar mat or local asphaltene deposition. The Flory-Huggins-Zuo Equation of State (FHZ EoS) is best used in conjunction with Downhole Fluid Analysis (DFA) to delineate these asphaltene gradients. This thermodynamic analysis of asphaltene gradient and GOR gradient using the Cubic EoS is best linked with high resolution analytical chemistry such as two-dimensional gas chromatography (GCxGC) and GC compositional analysis with geochemical interpretation. Fluid inclusion analysis is particularly useful to identify fluid type that occupied the reservoir in the geologic past. The stable isotope analysis of methane and other gases helps identify specific fluids that entered the reservoir.
The paper presents a case study from Gulf of Mexico and include data from three stacked reservoirs in a single reservoir. Each sand received two charges, an initial (light) black oil charge and a subsequent primary biogenic charge. Even with this simple scenario, three totally different fluids are found at the well location in each of the three sands. One sand currently contains a black oil with moderate GOR having received limited biogenic gas, a second sand contains a near critical fluid with both gas and oil phases, and the third sand contains a dry gas, the gas having blown out all the oil. The FHZ EoS is shown to apply for connectivity analysis as validated by many other methods. In the black oil column, some asphaltene instability caused by the late gas charge created a heavy oil at the oil-water contact. Lab measurements of Asphaltene Onset Pressure (AOP) confirmed this evaluation. The integration of asphaltene gradient modeling, DFA, gas isotopes, fluid inclusions, Cubic EoS, GCxGC with geochemical analysis provides a novel and systematic approach and should be considered for most conventional reservoirs.
D-X oilfield implemented an infill adjustment from 2013 to 2015, adding 101 development wells, two central processing platforms and two wellhead platforms. After the adjustment, the oil field greatly improved the engineering processing capacity, but it had also entered a period of rapid decline. In order to mitigate the decline and improve the recovery rate, 65 adjustment wells were implemented in this oilfield after the first adjustment. Based on the new drilling data and production data, earlier inefficient well management was turned a more efficient well management, where the engineering processing space is fully utilized, the decline of oil field is alleviated, and the development effect is greatly improved.
ABSTRACT With the fast pace of technology utilization, South China Sea has been having continuous exploration success, especially in shallow heavy oil reservoir with low resistivity contrast. The big uncertainty in this type of reservoir in this area is the well performance in the development stage due to formation laminations, various viscous fluid distribution, high connate water saturation and two-phase flow from the initial state of reservoir. To understand the key parameters that impact the later reservoir performance, the production forecasting analysis is needed from different advanced reservoir measurements, such as NMR, Dielectric measurement etc. to evaluate the uncertainty of the production potential, so that recommendations could be proposed to address these technical challenges and minimize the risks on later production. A case study from an appraisal well in offshore China is presented in this paper for the productivity uncertainty analysis in shallow heavy oil reservoir with low resistivity contrast formation. By analyzing the different reservoir measurements from various sources, an integrated approach is conveyed to tackle the challenges by integrating all available data in a numerical model, and the sensitivity study on permeability, fluid viscosity, completion skins etc. was carried to understand the impact severity of these parameters to reservoir production in the numerical model. Figure 1 Topography and bathymetry of PRMB,South China Sea and adjacent regions(Zicheng et al,2018) INTRODUCTION The Pearl River Delta depositional system (PRDS) is one of the most prominent depositional systems within the Pearl River Mouth Basin (PRMB), which is one of the most petroliferous basins in the northern margin of the South China Sea (Gong et al., 1997). Several shallow heavy oil reservoirs have been discovered in shallow formation in Enping sag with the large-scale reserves and reservoir capacity (Figure 1 and 2), many oil layers in these reservoirs have the characteristics of low resistivity below 2 ohm.m in the contrast with water layer 0.8-0.9
Reservoir heterogeneity is the key factor which impact production, the water flooding efficiency and ultimate hydrocarbon recovery during the reservoir development. Reliable productivity evaluation from early stage is needed to understand reservoir characteristics and minimize the uncertainty of production potential, so that the solution could be prepared for the technical challenges in the development phase. Evolution of wells drilled at high overbalance with water-based mud typically shows the following challenges: severe near-wellbore formation damage, complex pore structures due to complex the lithology system and big discrepancy among permeability from different measurement source. The productivity analysis becomes complicated and affected by the interpretation methods under different measurement environment.
A comprehensive case study is presented in this paper for the productivity evaluation in high heterogeneous reservoir at high overbalance drilling. An integrated approach is elaborated to overcome the challenges by integrating all available data from data acquisition. Different scaled permeability from open-hole logs, MDT pretests, mini-DST and DST is integrated systematically to understand the vertical and horizontal direction of reservoir heterogeneity. From the integrated data analysis, the interpreted reservoir properties are upscale and populated into numerical model and validated through history matching by dynamic tests. This integrated methodology or study provides the attractive and efficient way to evaluate the productivity in the early stage of reservoir lifecycle, and it minimizes the uncertainty of production potential by understanding the reservoir characteristics. At the end, the suggestions are concluded according to this comprehensive study.
Li, Maowen (CNOOC) | Lei, Guowen (Baker Hughes, a GE Company) | Zhang, Mingjie (CNOOC) | Coskun, Sefer B. (Baker Hughes, a GE Company) | Sy, Resksmey C. (Baker Hughes, a GE Company) | Hardikar, Nikhil P. (Baker Hughes, a GE Company)
The WEIZHOU-XYZ project is a newly developed offshore oilfield located in South China Sea. A quick and accurate productivity estimate would add valuable information to the decision-making on further field development, which is divided into three phases as per priority. A luxury dataset comprising seismic, drilling, well logs, well testing and production was acquired from most wells drilled in Phase-1. The objective of this paper is to establish a fast productivity forecasting method that can be used for the newly drilled wells of Phase-2 and Phase-3 after acquiring logging-while-drilling (LWD) data only.
The well-productivity forecasting model was based on uncertainty analyses using the Monte-Carlo method. Starting with equations of the production rate and the productivity index, each parameter of the equations has been investigated based on LWD data, and with a reference to the Phase-1 wells. Two key reservoir data used for the forecasting model are LWD formation testing (formation pressure while drilling - FPWD) and LWD nuclear magnetic resonance (NMR). These two dataset are the main information collected while drilling along with LWD resistivity and gamma ray in Phase 2. The FPWD data provides mobility, thus indicating the ability of fluid flow through the permeable reservoirs. The LWD NMR data provide continuous porosity measurement. Additionally, the T2 relaxation sensitives to both the pore size distribution and fluid properties providing estimation of formation permeability and fluid viscosity. Differing from the conventional way of a constant value input to the production rate equation, the proposed method sets all productivity related parameters (permeability, thickness, formation volume factor, viscosity, drainage radius etc.) under an uncertainty distribution range. The productivity prediction model is processed and evaluated using Monte-Carlo simulations. A scenario of 10,000 runs were conducted to account for the possible production distribution. As a result, an expected value of production rate or productivity index is used for the delivery of the possible forecasting outcome.
In this study, a successful application of this forecasting model has been proven by a good match with actual results from a well test. The observed difference is less than 5% between the real production rate and the expected value from the forecasting model.
This paper shows that formation testing while drilling and NMR while drilling together provide valuable inputs for productivity forecasting. The integrated method would be very helpful and meaningful for the production evaluation and decision-making for the Phase-2 and Phase-3 development wells, which will have limited data acquisition. A Monte-Carlo simulation workflow has been proposed for