Multifactor quantitative evaluation method for 3D porosity in geological period

A quantitative evaluation, geological period technology, applied in suspension and porous material analysis, measurement devices, seismic signal processing, etc. Consolidation, cementation, dissolution, and clay mineral transformation

Inactive Publication Date: 2017-04-26
CHINA UNIV OF PETROLEUM (EAST CHINA)
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the above three methods only evaluate 1D porosity evolution, and the acquisition of research data is too cumbersome and operators have strong subjective factors; moreover, the above three methods do not take into account In the past, only one point or a few points on the well surface were used to represent the overall reservoir quality of the target layer, and the contribution of

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  • Multifactor quantitative evaluation method for 3D porosity in geological period
  • Multifactor quantitative evaluation method for 3D porosity in geological period
  • Multifactor quantitative evaluation method for 3D porosity in geological period

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Experimental program
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Effect test

Embodiment 1

[0040] Embodiment 1: as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7, Figure 7, Figure 7, Figure 8 , Figure 9 , Figure 10 , Figure 11 , Figure 12 , Figure 13 as shown,

[0041] A multi-factor quantitative evaluation method for 3D porosity in geological periods belongs to the research field of 3D diagenetic numerical simulation of low-permeability-tight reservoirs, and provides technical means for the evaluation of oil and gas "sweet spots" in low-permeability-tight reservoirs.

[0042] A multi-factor quantitative evaluation method for 3D porosity in the geological period. Based on different rock types in the target layer, combined with the percentage content of different rock types, the initial porosity is evaluated by weighted summation, and the cementation of the target layer is carried out Porosity spatio-temporal distribution evaluation method for reducing porosity and increasing porosity correction by dissolution and dissol...

Embodiment 2

[0091] Embodiment 2: as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7, Figure 7, Figure 7, Figure 8 , Figure 9 , Figure 10 , Figure 11 , Figure 12 , Figure 13 as shown,

[0092] A method for quantitatively evaluating 3D porosity in geological time with multiple factors, comprising the following steps:

[0093] Step 1), well location selection: Based on the exploratory wells in the study area, establish a planar well location grid based on the exploration data in the study area. If the spacing is 0.5km×0.5km, the well location grid should be able to reflect the structure of the study area The range of change, or determined based on seismic data;

[0094] Step 2), arrange data: collect and organize the target layer mud logging data, well logging data, seismic data and rock whole-rock X-ray diffraction analysis test data; wherein the target layer rock whole-rock X-ray diffraction analysis test data is classified as feldspar sands...

Embodiment 3

[0102] Embodiment 3: as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7, Figure 7, Figure 7, Figure 8 , Figure 9 , Figure 10 , Figure 11 , Figure 12 , Figure 13 as shown,

[0103] A multi-factor quantitative evaluation method for 3D porosity in the geological period. Based on different rock types and their percentages in the target layer, the initial porosity is evaluated by weighted sum method, cementation and dissolution correction, and the evaluation of the spatial and temporal distribution of porosity method, including the following steps:

[0104] Step (1), well location selection: based on the exploratory wells in the target layer of the XX Sag in the XX Basin, a planar well location grid based on the exploration data in the study area is established. The well location grid should be able to reflect the range of structural changes in the study area. Or determined based on seismic data;

[0105] Such as figure 1 , there a...

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Abstract

A multifactor quantitative evaluation method for the 3D porosity in a geological period belongs to the technical field of diagenetic value simulation in a low-penetration compact reservoir. A planer grid well is selected, and well logging, logging, seismic and analysis and test data is collected and arranged; a 3D burial history and a thermal history under constraints of a sequence stratigraphic framework and deposition microfacies are established, 3D porosity evolution history models of mudstones, arkoses, quartz sandstones and rock-fragment sandstones are established on the basis of a target position, and porosity evolution histories of the different rock types in the target position are evaluated; on the basis of contribution of cementation and corrosion effects of the target position in a research region to the total porosity, porosity effect is corrected by decrease and increase, and a 3D porosity evolution process is evaluated; and a practically measured porosity of the grid well and the simulated porosity of a corresponding well point are analyzed by comparison, the precision requirement is met when the matching degree reaches 75%, and space-time distribution of the 3D porosity of the low-penetration compact reservoir in the geological period is evaluated.

Description

technical field [0001] The invention relates to a multi-factor quantitative evaluation method for 3D porosity in geological periods, and belongs to the technical field of diagenetic numerical simulation of low-permeability-tight reservoirs. Background technique [0002] At present, the research on reservoir porosity evolution has three aspects: 1. Based on the cast thin section, scanning electron microscope and cathodoluminescence microscope data, combined with the burial history of a single well to determine the diagenetic evolution stage and diagenetic evolution sequence, considering mechanical compaction and hot pressing For practical purposes, evaluate the porosity evolution process of sandstone reservoirs; 2. Establish a comprehensive porosity evolution model, including the initial porosity empirical formula and the porosity loss model, porosity increase model and fracture porosity model. Evaluate the reservoir pore evolution process; 3. Use stepwise regression analysis...

Claims

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Application Information

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IPC IPC(8): G01V1/48G01V1/50G01N15/08G01N23/20
CPCG01N15/088G01N23/20G01V1/48G01V1/50
Inventor 王文广林承焰卢双舫郑民
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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